{"id":"W2047864865","doi":"10.1520/jfs2004207","title":"A PCR Multiplex and Database for Forensic DNA Identification of Dogs","year":2005,"lang":"en","type":"article","venue":"Journal of Forensic Sciences","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"","keywords":"Microsatellite; Inbreeding; DNA profiling; Biology; Population; Loss of heterozygosity; Multiplex; Genetics; Forensic identification; Forensic science; Suspect; Evolutionary biology; Database; Allele; DNA; Medicine; Criminology; Computer science; Psychology; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002146933,0.0005416039,0.0006806516,0.005272328,0.0006271746,0.001095297,0.001075894,0.0008419886,0.008913165],"category_scores_gemma":[0.003387583,0.0004810413,0.0003650883,0.002041256,0.0004285492,0.00101727,0.00100688,0.0006032102,0.005948179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006528654,"about_ca_system_score_gemma":0.001293645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009002052,"about_ca_topic_score_gemma":0.001860436,"domain_scores_codex":[0.9972079,0.0004200135,0.0004100391,0.001073807,0.000733749,0.0001544697],"domain_scores_gemma":[0.9970856,0.0004918336,0.0007962588,0.00056278,0.000648716,0.0004147456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001339966,0.0006721541,0.04826603,0.001006266,0.0001544684,0.001268564,0.0007484469,0.001229257,0.3415814,0.00927349,0.03407423,0.5603858],"study_design_scores_gemma":[0.0002466007,0.001937903,0.1492405,0.0005872546,0.0003668712,0.01314523,0.000654073,0.01622978,0.2446415,0.006356738,0.5664373,0.00015632],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.359297,0.01162591,0.4457892,0.001353009,0.0006225018,0.003957878,0.1139281,0.01390511,0.04952108],"genre_scores_gemma":[0.2219461,0.002454645,0.5896041,0.0008936035,0.000155361,0.002707168,0.1466691,0.0006420195,0.03492782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008913165,"threshold_uncertainty_score":0.02981746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03852343319144338,"score_gpt":0.3183460362967306,"score_spread":0.2798226031052873,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}