{"id":"W6888810424","doi":"10.22008/fk2/cs5lka/m6nubu","title":"c50tfbw5.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":[0.0009738795,0.002925759,0.001920167,0.005231404,0.0009156312,0.003037871,0.003891932,0.002836697,0.2501043],"category_scores_gemma":[0.006768183,0.001088888,0.001468076,0.01148856,0.0005880554,0.001762837,0.002025033,0.001966521,0.2912717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001746041,"about_ca_system_score_gemma":0.002946107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06745792,"about_ca_topic_score_gemma":0.08074538,"domain_scores_codex":[0.998931,0.0001675986,0.0001059696,0.0003444637,0.0002237205,0.0002271676],"domain_scores_gemma":[0.997505,0.0007273725,0.0001548761,0.0006427701,0.0007211925,0.0002488036],"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":[0.00002408211,0.000005680445,0.0001275938,0.0002680188,0.00001167212,0.000005685772,0.000008619026,0.0001898772,0.00003340522,0.0002381425,0.9984283,0.0006590003],"study_design_scores_gemma":[0.0002375749,0.00001099483,0.001403213,0.0001935461,0.00002463585,0.00002667291,0.00005525982,0.0004812455,0.0002071713,0.0012507,0.9960819,0.00002722536],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002859503,0.00001857165,0.0000344008,0.00002355018,0.000009932738,0.000003298289,0.999143,0.0003347378,0.0004038816],"genre_scores_gemma":[0.0001436999,0.00002342829,0.0001289558,0.00002069548,0.000003573432,0.00002566632,0.9990873,0.0001580522,0.0004085257],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7498957,"threshold_uncertainty_score":0.8366824,"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."}}