{"id":"W2299960721","doi":"10.15200/winn.144703.34527","title":"Move over DNA: Here comes forensic pollen analysis","year":2015,"lang":"en","type":"dataset","venue":"The Winnower","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forensic science; Pollen; Computational biology; Computer science; Biology; Genetics; Botany","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004422608,0.0003211244,0.0004109276,0.0001304937,0.0001020552,0.00005987223,0.0008368604,0.0004236946,0.0004536207],"category_scores_gemma":[0.0001356353,0.0002075866,0.0003231123,0.0004204488,0.0003368529,0.000001856009,0.0005684164,0.0002910513,0.0002886329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002629557,"about_ca_system_score_gemma":0.000228934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003165838,"about_ca_topic_score_gemma":0.0005914498,"domain_scores_codex":[0.9981569,0.000140031,0.0002698078,0.0004892532,0.0005209035,0.0004230723],"domain_scores_gemma":[0.9976903,0.00002917526,0.0001348415,0.001781868,0.0002350358,0.0001287294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006079505,0.00002929241,0.0001395361,0.00001350573,0.001329603,0.000005712845,0.00001374265,0.00002832412,0.0001847154,0.000004793276,0.9978809,0.0003090829],"study_design_scores_gemma":[0.0003300816,0.0001150864,0.0006897642,0.000007378314,0.0005074641,0.000006090049,0.00007904576,0.00001363487,0.0005198634,0.0001327035,0.9973233,0.0002756338],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0119739,0.002908441,0.00002021076,0.0005727834,0.0003063368,0.0003392704,0.9825198,0.000008821143,0.001350449],"genre_scores_gemma":[0.003963848,0.0004903483,0.00003232275,0.0007360714,0.0007304937,0.00002430161,0.980544,0.0000291111,0.01344953],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01209908,"threshold_uncertainty_score":0.8465134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01490287073527509,"score_gpt":0.2995901337970567,"score_spread":0.2846872630617816,"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."}}