{"id":"W6964092345","doi":"10.22008/fk2/cs5lka/q2ogtk","title":"w50acbw8.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":[0.0009221846,0.002620023,0.001889207,0.00474969,0.0007263941,0.002929763,0.003157086,0.002265249,0.2288491],"category_scores_gemma":[0.005227564,0.00114212,0.001190475,0.01029933,0.0004439543,0.001637355,0.001853508,0.001692929,0.2972131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136035,"about_ca_system_score_gemma":0.001957942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04770355,"about_ca_topic_score_gemma":0.06712823,"domain_scores_codex":[0.9990901,0.0001514715,0.00009289541,0.0002864651,0.0001859829,0.0001930975],"domain_scores_gemma":[0.9982325,0.0004695551,0.0001540833,0.0004686089,0.000499927,0.0001753095],"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":[0.00002155289,0.000005429183,0.0001772638,0.0002637261,0.0000137555,0.000006299812,0.00001147949,0.0001614867,0.00003467032,0.0002675393,0.9981632,0.0008736386],"study_design_scores_gemma":[0.0001756284,0.000008735282,0.001604566,0.0001705296,0.0000208249,0.00001970215,0.00005509917,0.0003115294,0.0001499891,0.001119585,0.9963424,0.00002146103],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002842918,0.00001769126,0.00003806538,0.00002183215,0.000009095268,0.000002805121,0.9992158,0.000239894,0.0004263285],"genre_scores_gemma":[0.0001603384,0.00002767469,0.0001547379,0.00001987663,0.000004299872,0.00003224108,0.9987524,0.0001605791,0.0006878045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7711509,"threshold_uncertainty_score":0.7655765,"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."}}