{"id":"W6888774123","doi":"10.22008/fk2/cs5lka/ki288d","title":"w50ac13.rtl","year":2022,"lang":"fr","type":"dataset","venue":"Geological Survey of Denmark and Greenland (GEUS)","topic":"","field":"","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":[0.0009617781,0.002961198,0.002092302,0.004643613,0.0007654863,0.003013422,0.003578411,0.002409606,0.2563459],"category_scores_gemma":[0.004861739,0.001271955,0.001541786,0.009094073,0.0004612755,0.001741715,0.001961814,0.001763077,0.3272547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087297,"about_ca_system_score_gemma":0.001914514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04522093,"about_ca_topic_score_gemma":0.06763246,"domain_scores_codex":[0.9990512,0.0001583094,0.00009440628,0.0002981708,0.0001903554,0.0002075577],"domain_scores_gemma":[0.9983346,0.0004395318,0.0001420885,0.0004699234,0.0004461927,0.0001677655],"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":[0.00002287192,0.000006123273,0.0001738089,0.0002775983,0.00001705833,0.000006791097,0.00001130032,0.000202187,0.00004037786,0.0002650674,0.9980845,0.0008922074],"study_design_scores_gemma":[0.0002383759,0.00001113104,0.001635236,0.0001849805,0.00002809232,0.00002330473,0.00005455773,0.0004041055,0.0001839977,0.001327834,0.9958817,0.0000266743],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002722588,0.00001763435,0.00004649295,0.00002146275,0.00001086369,0.000003018942,0.9990656,0.0003388809,0.0004688866],"genre_scores_gemma":[0.0001571479,0.00002570169,0.0001738514,0.00002118424,0.000004887556,0.00002991205,0.9987046,0.000210487,0.0006722947],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7436541,"threshold_uncertainty_score":0.8575625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04542538225107298,"score_gpt":0.2735741399171185,"score_spread":0.2281487576660455,"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."}}