{"id":"W4253103226","doi":"10.4095/219889","title":"Mine Tailings Characterization Using PROBE Data (Preliminary Results)","year":2002,"lang":"en","type":"report","venue":"","topic":"Tailings Management and Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Tailings; Characterization (materials science); Mining engineering; Geology; Environmental science; Metallurgy; Materials science; Nanotechnology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001241029,0.0002342077,0.0001592441,0.0003401108,0.0002743207,0.0003350766,0.000252863,0.0003185151,0.001593644],"category_scores_gemma":[0.0004472436,0.0001104511,0.0001190483,0.0004753099,0.0001596217,0.0003808627,0.0002037541,0.000193791,0.000355315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005225873,"about_ca_system_score_gemma":0.0007060304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09602878,"about_ca_topic_score_gemma":0.2078207,"domain_scores_codex":[0.9998873,0.000006529485,0.00000289208,0.00002344054,0.00005790867,0.00002185458],"domain_scores_gemma":[0.9998288,0.00001916932,0.00001022227,0.0000153061,0.0001112801,0.00001505227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004828273,0.0002046066,0.1128548,0.0001088418,0.00002264263,0.000381431,0.0005801085,0.008498487,0.7518835,0.0002347527,0.002605621,0.1221423],"study_design_scores_gemma":[0.00007564273,0.0005698816,0.5214983,0.0000155777,0.00005454206,0.0005852739,0.001344675,0.06271057,0.4005983,0.0002684422,0.01222056,0.00005827595],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793985,0.00005435267,0.01377225,0.00006142235,0.000004663059,0.000112256,0.002337565,0.0003383984,0.003920493],"genre_scores_gemma":[0.9761906,0.00006845065,0.01865826,0.00003069869,0.000002212982,0.00005544022,0.002229284,0.00003178555,0.00273325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09602878,"threshold_uncertainty_score":0.1909397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1013847758530394,"score_gpt":0.2628645433830166,"score_spread":0.1614797675299772,"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."}}