[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128522-en":3,"doc-seo-128522-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},128522,687207020761,"Patrick","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Bullet Ricochet Mark Plan-View Morphology in Concrete - An Experimental Assessment of Five Bullet Types and Two Distances","Bullet ricochets are frequent in shooting incidents and can yield valuable clues for reconstruction. A controlled experiment analyzed the plan-view morphology of 297 ricochet impact sites in concrete produced by five bullet types fired from two distances. A random forest machine learning model classified bullet types from ricochet-mark morphometrics, with length and perimeter-to-area ratio as key predictors. Distinguishability was strongest for .22 LR, and adding distance improved accuracy from 62% to 66% using leave-one-out cross-validation, though overlap across bullet types suggests potential error in real-case human identification.","Bullet ricochet mark plan-view morphology in concrete: an experimental assessment of five bullet types and two distances using machine learning  \nMetin I. Eren 1,2 *, Jay Romans3, Robert S. Walker4, Briggs Buchanan5, Alastair Key6  \n1. Department of Anthropology, Kent State University, Kent, Ohio, USA  \n2. Department of Archaeology, Cleveland Museum of Natural History, Cleveland, Ohio, 44106, USA  \n3. Pro Armament, Cuyahoga Falls, Ohio, USA  \n4. Department of Anthropology, University of Missouri, Columbia, Missouri  \n5. Department of Anthropology, University of Tulsa, Tulsa, Oklahoma, USA  \n6. Department of Archaeology, University of Cambridge, Cambridge, UK  \n© The Author(s) 2023. Published by OUP on behalf of the Academy of Forensic Science.  \nDownloaded from on 02 January[https://academic.oup.com/fsr/advance-article/doi/10.1093/fsr/owad051/7503845 by University of Cambridge user](https://academic.oup.com/fsr/advance-article/doi/10.1093/fsr/owad051/7503845 by University of Cambridge user) 2024  \nAbstract  \nBullet ricochets are common occurrences during shooting incidents and can provide a wealth of  \ninformation useful for shooting incident reconstruction. However, there have only been a small number  \nof studies that have systematically investigated bullet ricochet impact site morphology. Here, this study  \nreport on an experiment that examined the plan-view morphology of 297 ricochet impact sites in  \nconcrete that were produced by five different bullet types shot from two distances. This study used a  \nrandom forest machine learning algorithm to classify bullet types with morphological dimensions of the  \nricochet mark (impact) with length and perimeter-to-area ratio emerging as the top predictor variables.  \nThe .22 LR leaves the most distinctive impact mark on the concrete, and overall, the classification  \naccuracy using leave-one-out cross-validation is 62%, considerably higher than a random classification  \naccuracy of 20%. Adding in distance to the model as a predictor increases the classification accuracy to  \n66%. These initial results are promising, in that they suggest that an unknown bullet type can potentially  \nbe determined, or at least probabilistically assessed, from the morphology of the ricochet impact site  \nalone. However, the substantial amount of overlap this study documented among distinct bullet types’  \nricochet mark morphologies under highly controlled conditions and with machine learning suggests that  \nthe human identification of ricochet marks in real-world shooting incident reconstructions may be on  \noccasion, or perhaps regularly, in error.  \nKey Points  \nBullet ricochet impact sites can help with shooting incident reconstruction.  \nA random forest machine learning algorithm classified bullet type from ricochet morphology.  \nResults suggest that unknown bullets can potentially be determined from ricochet impact site  \nmorphology.  \nHuman identification of bullet types from ricochet sites may be erroneous.  \nKeywords  \nBullet ricochet; Machine Learning; Morphometrics; Concrete; Shooting incident reconstruction  \nIntroduction  \nBullet ricochet is a type of deflection that changes the initial bullet path and velocity by impact, but without perforation or penetration ([1]: p.263-264; [2-5]; [6]: p.605; [7]: p.21, 163) . Ricochets are common occurrences during shooting incidents, can occur accidentally or intentionally, and are affected  \nDownloaded from on 02 January[https://academic.oup.com/fsr/advance-article/doi/10.1093/fsr/owad051/7503845 by University of Cambridge user](https://academic.oup.com/fsr/advance-article/doi/10.1093/fsr/owad051/7503845 by University of Cambridge user) 2024  \nby a wide range of factors [8,9] . As such, the phenomenon of bullet ricochet has a rich and diverse research history [1, 10-11] . Ricochet experiments and case studies include the investigation of wound production; bullet destabilization; bullet deformation and fragmentation; bullet path and velocity change;","cbCaitbEc60BYlxV","https://ap.wps.com/l/cbCaitbEc60BYlxV","pdf",1232960,1,22,"English","en",105,"# Abstract\n# Key Points\n# Keywords\n# Introduction","[{\"question\":\"What problem does the study address about bullet ricochets?\",\"answer\":\"It targets the limited systematic research on bullet ricochet impact site morphology and its value for shooting incident reconstruction.\"},{\"question\":\"How does the study classify bullet types from ricochet marks?\",\"answer\":\"It applies a random forest machine learning algorithm using morphometric dimensions of the ricochet mark, especially length and perimeter-to-area ratio.\"},{\"question\":\"What accuracy results are reported, and how does adding distance change them?\",\"answer\":\"Overall accuracy is 62% with leave-one-out cross-validation, improving to 66% when distance is included as a predictor.\"}]","Bullet Ricochet Mark Plan-View Morphology in Concrete - An Experimental Assessment of Five Bullet Types and Two Distances | PDF",1786001531,55,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"bullet-ricochet-mark-plan-view-morphology-in-concrete-an-experimental-assessment-of-five-bullet-types-and-two-distances","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/bullet-ricochet-mark-plan-view-morphology-in-concrete-an-experimental-assessment-of-five-bullet-types-and-two-distances/128522/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-24","2026-08-06",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the study address about bullet ricochets?","Question",{"text":76,"@type":77},"It targets the limited systematic research on bullet ricochet impact site morphology and its value for shooting incident reconstruction.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does the study classify bullet types from ricochet marks?",{"text":81,"@type":77},"It applies a random forest machine learning algorithm using morphometric dimensions of the ricochet mark, especially length and perimeter-to-area ratio.",{"name":83,"@type":74,"acceptedAnswer":84},"What accuracy results are reported, and how does adding distance change them?",{"text":85,"@type":77},"Overall accuracy is 62% with leave-one-out cross-validation, improving to 66% when distance is included as a predictor.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]