{"id":"W6963259193","doi":"10.22008/fk2/cs5lka/hxlxql","title":"w50z10_11.rtl","year":2022,"lang":"cs","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":[0.0008647643,0.002416639,0.001723606,0.004174843,0.0007873323,0.002899954,0.003546953,0.002242856,0.2721382],"category_scores_gemma":[0.005243889,0.001298913,0.001284971,0.009905295,0.0005101811,0.001674621,0.002090327,0.001717424,0.2795554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001311241,"about_ca_system_score_gemma":0.002630679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06099886,"about_ca_topic_score_gemma":0.08135948,"domain_scores_codex":[0.9990906,0.0001316628,0.00009454128,0.0002985331,0.0001829511,0.0002017427],"domain_scores_gemma":[0.998095,0.0005761622,0.000148672,0.0004655629,0.000519508,0.0001951482],"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":[0.00002814494,0.00000711026,0.0002260417,0.0003013282,0.00001681567,0.000007515176,0.00001349867,0.0002067222,0.00004060314,0.0003248408,0.9980353,0.000792178],"study_design_scores_gemma":[0.000256296,0.00001158895,0.002194828,0.0001845886,0.00002542261,0.00002047439,0.00007387661,0.0003615406,0.0002131356,0.001176605,0.9954526,0.00002895617],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002923926,0.00001114645,0.00002766349,0.00001946135,0.000009487014,0.00000274394,0.9993179,0.0001911867,0.0003911977],"genre_scores_gemma":[0.0001860903,0.0000219274,0.000121012,0.00002179201,0.000004215543,0.00003406159,0.9987171,0.0001553894,0.0007385697],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7278618,"threshold_uncertainty_score":0.910393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04514387088436098,"score_gpt":0.2783582525751909,"score_spread":0.2332143816908299,"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."}}