{"id":"W4394364156","doi":"10.6084/m9.figshare.21382490","title":"Additional file 3 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":[0.00197748,0.001529799,0.001392082,0.00411957,0.0009419167,0.002548957,0.002817748,0.002003595,0.5986392],"category_scores_gemma":[0.01568976,0.0007729922,0.001143841,0.006334991,0.0005097958,0.002127373,0.002464684,0.001416712,0.1882372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001659111,"about_ca_system_score_gemma":0.002334021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01463323,"about_ca_topic_score_gemma":0.02203257,"domain_scores_codex":[0.9990741,0.0001690172,0.0001667259,0.0002748162,0.0001821319,0.000133255],"domain_scores_gemma":[0.9908126,0.005632986,0.0006903344,0.0009589912,0.001448245,0.0004568642],"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":[0.0001036917,0.00002105135,0.0007724451,0.00126055,0.00002677899,0.0000248055,0.00002251845,0.0001762374,0.00006101206,0.0004793468,0.9948077,0.002243756],"study_design_scores_gemma":[0.001058646,0.00003666627,0.006778075,0.001411827,0.00008808171,0.0001374383,0.0001338003,0.0003850635,0.00038606,0.004587322,0.9849344,0.00006249939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002629484,0.00001091414,0.00005339805,0.00003657671,0.000006937191,0.00001245912,0.999366,0.0001244876,0.0003630276],"genre_scores_gemma":[0.0006157528,0.00005138592,0.0005435508,0.0001300739,0.00001213031,0.0001823613,0.996992,0.000248472,0.0012243],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5986392,"threshold_uncertainty_score":0.5724925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01674910943556998,"score_gpt":0.2524893391304313,"score_spread":0.2357402296948613,"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."}}