{"id":"W6927112764","doi":"10.25625/sq3iag","title":"IMPERIAL METALS CORP DEEPDIVE","year":2025,"lang":"en","type":"dataset","venue":"Göttingen Research Online","topic":"Diatoms and Algae Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tailings; Stock (firearms); Profit (economics); Copper mine; Drilling; Imperial unit system; Grading (engineering)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000397123,0.001471576,0.0008192006,0.001595937,0.001903902,0.004922372,0.001441387,0.00108902,0.8521116],"category_scores_gemma":[0.001133286,0.0006887226,0.0007546225,0.001187814,0.0004732064,0.002680371,0.002829395,0.001631485,0.777146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001402748,"about_ca_system_score_gemma":0.001218038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005181883,"about_ca_topic_score_gemma":0.01386191,"domain_scores_codex":[0.9994639,0.00003253975,0.00002092159,0.0001329253,0.0002869322,0.00006282641],"domain_scores_gemma":[0.9991446,0.00006418425,0.00002353818,0.0001878804,0.00038239,0.0001974233],"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":[0.0000774239,0.00004248804,0.0001936597,0.0001859288,0.00000522481,0.0001297209,0.0001035889,0.0001512023,0.001316579,0.005949219,0.8375387,0.1543063],"study_design_scores_gemma":[0.000006507228,0.00001669172,0.0002798524,0.00003183899,0.000002722532,0.00009466034,0.00005766308,0.00009160884,0.0005125449,0.0004880538,0.998412,0.000005877199],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.0007374227,0.0003622946,0.001341622,0.0005030041,0.0008989215,0.00004366917,0.001493629,0.003563002,0.9910564],"genre_scores_gemma":[0.001452934,0.0001670929,0.0006203424,0.0001249003,0.00005572847,0.00001234005,0.0007765051,0.001112593,0.9956775],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.8521116,"threshold_uncertainty_score":0.2109448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0796092006859699,"score_gpt":0.4368406869387197,"score_spread":0.3572314862527499,"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."}}