{"id":"W6945073433","doi":"10.22008/fk2/wp1tr3/aemles","title":"w50tfbw8.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":[0.0008953767,0.002509708,0.001802298,0.004520732,0.0006801789,0.002697691,0.002978491,0.002221701,0.2239634],"category_scores_gemma":[0.00539392,0.001093292,0.001164059,0.009685494,0.0004418826,0.001608826,0.001886627,0.001645958,0.2937623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093902,"about_ca_system_score_gemma":0.001818842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04095138,"about_ca_topic_score_gemma":0.05514792,"domain_scores_codex":[0.9991333,0.0001428473,0.00009195707,0.0002707729,0.0001770434,0.0001841408],"domain_scores_gemma":[0.9983048,0.0004814968,0.0001435241,0.0004371591,0.0004613225,0.0001717373],"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":[0.00002408635,0.000006191884,0.0001770391,0.0002884323,0.00001351221,0.000007397489,0.00001290225,0.0001779859,0.00004156069,0.00027258,0.9979749,0.001003444],"study_design_scores_gemma":[0.0001938891,0.00001011961,0.001677736,0.0001896214,0.00002068886,0.00002347062,0.0000625605,0.0003461944,0.0001714961,0.001216784,0.9960656,0.00002197895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003124867,0.00001703464,0.00004250771,0.00002326872,0.000009319884,0.000002854005,0.9991997,0.0002510644,0.0004230379],"genre_scores_gemma":[0.0001500944,0.00002613682,0.0001468119,0.00001768614,0.000003941282,0.00003100644,0.9988521,0.0001474197,0.0006246678],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7760366,"threshold_uncertainty_score":0.7492321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04553673280496227,"score_gpt":0.2736657331203128,"score_spread":0.2281290003153505,"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."}}