{"id":"W4394336274","doi":"10.6084/m9.figshare.3506666.v1","title":"Till geochemistry and mineralogy: vectoring towards Cu porphyry deposits in British Columbia, Canada","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geochemistry; Geology; Porphyry copper deposit; Earth science; Fluid inclusions; Seismology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002896208,0.001527056,0.0008795522,0.002843098,0.001190302,0.001657585,0.001942462,0.001061157,0.01261898],"category_scores_gemma":[0.002141363,0.0005398212,0.0008443394,0.007657721,0.0004535377,0.0005257271,0.00126028,0.001137935,0.009511437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005824969,"about_ca_system_score_gemma":0.01093321,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9406999,"about_ca_topic_score_gemma":0.9749147,"domain_scores_codex":[0.9996752,0.00001490433,0.0000267686,0.00009708735,0.0001000359,0.00008605828],"domain_scores_gemma":[0.9988074,0.0001226392,0.00007297235,0.0001685057,0.0006597282,0.0001686819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001298042,0.00003817507,0.01869322,0.0008647665,0.0001188957,0.0001112084,0.00017463,0.002269526,0.0004608476,0.0005282027,0.9662232,0.01038748],"study_design_scores_gemma":[0.0002281182,0.00001793724,0.1426621,0.0007245697,0.0001333227,0.0001275072,0.0007882806,0.003952924,0.001463843,0.001169221,0.848635,0.00009713523],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001649214,0.00008903324,0.00005414429,0.00004548883,0.000008845272,0.000006692073,0.9973507,0.0002560073,0.0005399094],"genre_scores_gemma":[0.00442624,0.0001276245,0.000295205,0.00001863773,0.000003030745,0.0000267696,0.993996,0.00004542364,0.001060992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05930007,"threshold_uncertainty_score":0.1192985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01344709166585683,"score_gpt":0.198549693791523,"score_spread":0.1851026021256662,"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."}}