{"id":"W4394328030","doi":"10.6084/m9.figshare.21382484","title":"Additional file 1 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; Computational biology; Political science; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001660511,0.0002156544,0.0001866463,0.0001766668,0.000186763,0.00004691873,0.0003589165,0.0001264331,0.9206221],"category_scores_gemma":[0.002415586,0.0001958864,0.0000747155,0.0004277329,0.00004608504,0.000006289324,0.0004920911,0.0004251227,0.00007766192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005751793,"about_ca_system_score_gemma":0.0001433155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006760047,"about_ca_topic_score_gemma":0.00109355,"domain_scores_codex":[0.9982111,0.0003703593,0.0002806562,0.000438345,0.00042491,0.0002745588],"domain_scores_gemma":[0.9988192,0.0003141424,0.0002367799,0.000463619,0.0001119206,0.00005438061],"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":[0.00005411955,0.0000204324,0.000003236303,0.0001390145,0.00002228564,0.00001352615,0.0000120909,0.00005276394,0.00009360148,7.02388e-7,0.999342,0.0002462613],"study_design_scores_gemma":[0.0002275394,0.0002743985,0.00222088,0.0006295075,0.000005388168,0.000006215678,0.0001110622,0.00003124092,0.0002266253,0.000004981781,0.9960678,0.0001943913],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006501516,0.0002216921,3.419079e-7,0.00003037453,0.0000447298,0.0003128084,0.997819,0.000005264959,0.001500765],"genre_scores_gemma":[0.0001584006,0.00001896302,0.0001928608,0.0001097928,0.0002500274,0.0002593099,0.9978232,0.00002267782,0.001164721],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9205444,"threshold_uncertainty_score":0.7988015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0170146292020042,"score_gpt":0.2528283256364039,"score_spread":0.2358136964343997,"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."}}