{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007371735,0.0005230609,0.000971483,0.001074852,0.0007090091,0.0008594268,0.00319475,0.0006220305,0.01443132],"category_scores_gemma":[0.004686366,0.0004389017,0.0002755792,0.001312537,0.0007234481,0.0001958669,0.003452601,0.002189424,0.002149543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003006796,"about_ca_system_score_gemma":0.002353843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00340316,"about_ca_topic_score_gemma":0.0008959468,"domain_scores_codex":[0.990787,0.001502632,0.000836955,0.001388316,0.003324039,0.002161114],"domain_scores_gemma":[0.9944816,0.001540534,0.0002176795,0.001903243,0.001313964,0.0005429647],"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":[0.000131784,0.0004373266,0.000004138168,0.0004612982,0.0000795298,0.0002258659,0.00001712289,0.000003009041,0.006654029,0.00007622239,0.9905396,0.001370045],"study_design_scores_gemma":[0.0005282128,0.0002483085,0.0000200705,0.0002725623,0.0000508626,0.000007123941,0.00007171441,0.00003412538,0.004727481,0.0003798122,0.9932587,0.0004010892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005858728,0.001780468,0.000003835129,0.0007000092,0.001226147,0.001022276,0.9884664,0.00009319567,0.0008489394],"genre_scores_gemma":[0.00008903963,0.002010757,0.0008315497,0.0001655502,0.002487308,0.0002005194,0.988774,0.00003566812,0.005405619],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01228178,"threshold_uncertainty_score":0.9998063,"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."}}