{"id":"W6926409621","doi":"10.22008/fk2/cs5lka/lnf4xv","title":"chrisz10.gsf","year":2022,"lang":"hu","type":"dataset","venue":"Geological Survey of Denmark and Greenland (GEUS)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Apotex Pharmachem (Canada)","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":[0.001070701,0.004066817,0.00206087,0.005174376,0.001142059,0.002991642,0.003679166,0.00244181,0.2536203],"category_scores_gemma":[0.005260159,0.001078377,0.001461873,0.006616681,0.0006746681,0.001214327,0.002716902,0.001445055,0.3457287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157623,"about_ca_system_score_gemma":0.002336578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02533969,"about_ca_topic_score_gemma":0.04360739,"domain_scores_codex":[0.9989969,0.000168159,0.00005768685,0.0003627535,0.000189713,0.0002248307],"domain_scores_gemma":[0.9982997,0.0004027035,0.0001398726,0.0005262367,0.0002882791,0.0003433378],"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":[0.00004430644,0.00001464787,0.000309649,0.0002788363,0.00001442571,0.000007582772,0.00001541293,0.000197017,0.00006768442,0.0001947939,0.9970909,0.001764654],"study_design_scores_gemma":[0.000351257,0.0000254891,0.001730584,0.0001544023,0.000034614,0.00003576928,0.00007997178,0.0006401152,0.0003616627,0.001225177,0.9953297,0.00003124151],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001167704,0.00003834755,0.00005044431,0.0000350759,0.00001688983,0.000008827382,0.9980007,0.0009710547,0.0007619091],"genre_scores_gemma":[0.0003672253,0.00003793445,0.0002525102,0.00003885364,0.000006591982,0.00005549023,0.9978341,0.000263057,0.001144132],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7463797,"threshold_uncertainty_score":0.8484444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715127517586906,"score_gpt":0.2614189879443947,"score_spread":0.2442677127685256,"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."}}