{"id":"W6963895634","doi":"10.22008/fk2/wp1tr3/fxbyhv","title":"c50vg4.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":[0.0009921895,0.003501378,0.002309319,0.005140225,0.0009434277,0.003403457,0.004662752,0.003116134,0.2459046],"category_scores_gemma":[0.005606825,0.001273707,0.001801843,0.01145709,0.0006321821,0.001956233,0.002148765,0.002245176,0.3067079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639724,"about_ca_system_score_gemma":0.002849578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06514667,"about_ca_topic_score_gemma":0.08566852,"domain_scores_codex":[0.9988977,0.0001710158,0.00009849822,0.0003604967,0.0002386301,0.0002336426],"domain_scores_gemma":[0.997898,0.000598572,0.0001284003,0.0005849197,0.0005803601,0.0002097277],"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":[0.00002140305,0.000005492387,0.0001185343,0.0002504897,0.00001370213,0.000005141446,0.000008066043,0.000224538,0.00003010795,0.0002153366,0.9984702,0.0006368501],"study_design_scores_gemma":[0.0002732215,0.00001096491,0.001253262,0.0002010701,0.00003052065,0.00002568469,0.00005115075,0.0006646619,0.0001979902,0.001427683,0.9958299,0.00003391431],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002660488,0.00002053199,0.00003986248,0.0000266794,0.00001226363,0.00000376939,0.9988644,0.0005429563,0.0004628709],"genre_scores_gemma":[0.000140836,0.00002575992,0.000160085,0.00002461568,0.000004350768,0.00002697586,0.9989645,0.0002484669,0.0004044309],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7540954,"threshold_uncertainty_score":0,"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."}}