{"id":"W6907397696","doi":"10.22008/fk2/cs5lka/ty1vto","title":"w50acbw9.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":[0.0009085723,0.002613652,0.001814862,0.005066914,0.0007734479,0.003078558,0.003590401,0.002296409,0.2490037],"category_scores_gemma":[0.005853783,0.001128489,0.001249616,0.01168168,0.0005127342,0.001737051,0.001963432,0.001821565,0.3009279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275631,"about_ca_system_score_gemma":0.002480883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05477964,"about_ca_topic_score_gemma":0.07528975,"domain_scores_codex":[0.9990516,0.0001484417,0.00009982952,0.0003047732,0.0001969446,0.0001984147],"domain_scores_gemma":[0.9978523,0.0005707323,0.00016562,0.0005725793,0.0006181908,0.0002205567],"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":[0.00002213336,0.000005373505,0.0001593429,0.0002358365,0.0000124608,0.000005482802,0.000008938406,0.0001485449,0.00003122546,0.0002593356,0.9984385,0.0006728057],"study_design_scores_gemma":[0.0002117849,0.000009708227,0.00161379,0.0001609094,0.00002232412,0.00001983285,0.00005756629,0.0003651587,0.0001738166,0.001198075,0.996143,0.00002397517],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002768357,0.00001427636,0.00003075291,0.0000208337,0.000009785411,0.0000028575,0.9992664,0.0002391329,0.0003883171],"genre_scores_gemma":[0.0001558325,0.00002394359,0.0001287295,0.00002003529,0.000004180667,0.00002850425,0.9988816,0.0001525565,0.0006045954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7509963,"threshold_uncertainty_score":0.8330004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04526660351752165,"score_gpt":0.278450120105301,"score_spread":0.2331835165877793,"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."}}