{"id":"W4394121376","doi":"10.6084/m9.figshare.21382496","title":"Additional file 4 of The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Agriculture and Agri-Food Canada","funders":"","keywords":"Suspect; Computer science; Political science; Law","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002219667,0.001281888,0.001485757,0.004854569,0.0009427238,0.002698377,0.002671289,0.001954239,0.6515138],"category_scores_gemma":[0.02248107,0.0007320229,0.001084259,0.008030239,0.0005057594,0.002244641,0.00246094,0.001312189,0.1956668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001721078,"about_ca_system_score_gemma":0.002659572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01359693,"about_ca_topic_score_gemma":0.02022175,"domain_scores_codex":[0.9988403,0.0002177429,0.0002420712,0.0003259307,0.0002251733,0.0001488671],"domain_scores_gemma":[0.9855676,0.009093013,0.001107341,0.001355997,0.002277566,0.0005986291],"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":[0.00009488213,0.00001896984,0.0007686808,0.001653412,0.00002674046,0.00002283144,0.00002345912,0.0001409083,0.00004436936,0.000539693,0.9941202,0.002545888],"study_design_scores_gemma":[0.0009447121,0.00003217737,0.005765041,0.001856584,0.00008055487,0.0001112995,0.0001301622,0.0002359291,0.0002449928,0.004173305,0.986375,0.00005027446],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002387857,0.00001382463,0.00004316315,0.00004463896,0.00000749948,0.00001231198,0.9993646,0.00008272042,0.0004074765],"genre_scores_gemma":[0.0007370457,0.00007753854,0.0005409463,0.0001605919,0.00001781009,0.0002198939,0.9962967,0.0002020623,0.001747328],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6515138,"threshold_uncertainty_score":0.4970732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686426849209448,"score_gpt":0.25283105381265,"score_spread":0.2359667853205555,"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."}}