{"id":"W2151280747","doi":"10.1016/j.fsigen.2014.11.023","title":"Inclusion probability with dropout: An operational formula","year":2014,"lang":"en","type":"article","venue":"Forensic Science International Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; Université du Québec à Trois-Rivières","funders":"","keywords":"Inclusion (mineral); Dropout (neural networks); Interpretation (philosophy); Locus (genetics); Context (archaeology); Mathematics; Statistics; Computer science; Genetics; Psychology; Biology; Machine learning; Social 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007625743,0.0001404794,0.00009000327,0.00009145986,0.0004182761,0.0001086173,0.0007725169,0.00006767679,0.0000534448],"category_scores_gemma":[0.000207615,0.0001088608,0.00003633377,0.0001957975,0.0010315,0.00002023627,0.000782268,0.00008186517,0.00001476894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004448284,"about_ca_system_score_gemma":0.0003108247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002388134,"about_ca_topic_score_gemma":0.0001374403,"domain_scores_codex":[0.9979078,0.0000376031,0.0002033512,0.0005529289,0.0009878919,0.0003103924],"domain_scores_gemma":[0.9985216,0.00001222219,0.00005913447,0.0004682945,0.0007602088,0.0001785736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005088652,0.0004352596,0.07553875,0.00001940248,0.00007004791,0.000004520693,0.0008508985,0.01507084,0.7028091,0.02478404,0.002025664,0.1778826],"study_design_scores_gemma":[0.001627665,0.00334284,0.04994151,0.000030575,0.00001589226,0.000124335,0.0001336863,0.1346005,0.7112453,0.01902605,0.07921396,0.0006977011],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750402,0.00003026319,0.0180875,0.0005121547,0.0003022582,0.0001994875,0.00001121835,0.00001205154,0.005804898],"genre_scores_gemma":[0.9668236,0.000015977,0.03165366,0.0004359985,0.0003915972,0.00001633742,0.0001306713,0.00001362333,0.0005184966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1771849,"threshold_uncertainty_score":0.4439213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400469918471686,"score_gpt":0.3018072108046478,"score_spread":0.287802511619931,"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."}}