{"id":"W6969512524","doi":"10.5281/zenodo.840007","title":"Analysis On Industry And Trade - Operational Report","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Context (archaeology); Work (physics); Raw material; Production (economics); Outcome (game theory)","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":[0.003477208,0.0009258951,0.0005031892,0.01145013,0.0006565637,0.00256378,0.0009075251,0.0005233049,0.01431599],"category_scores_gemma":[0.008377356,0.0002755372,0.0008136166,0.01710947,0.0003717611,0.001821641,0.0009767718,0.0009215601,0.007815556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003271474,"about_ca_system_score_gemma":0.008643582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05485773,"about_ca_topic_score_gemma":0.02356714,"domain_scores_codex":[0.9920943,0.0008155372,0.0005534412,0.000475417,0.005301877,0.0007593712],"domain_scores_gemma":[0.9879511,0.002384001,0.001435541,0.0008344057,0.007072127,0.0003227633],"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":[0.0009919395,0.0007831661,0.190224,0.002365714,0.0004721999,0.0008174966,0.002127983,0.02090391,0.005996623,0.101929,0.3908185,0.2825695],"study_design_scores_gemma":[0.00003575913,0.0003119973,0.2497166,0.000365972,0.0001286346,0.0002797468,0.003720926,0.004523735,0.006250085,0.008277321,0.726305,0.00008422183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1240347,0.001950286,0.01425061,0.001124023,0.0002473801,0.001473077,0.6389725,0.0005906067,0.2173569],"genre_scores_gemma":[0.1915488,0.002467995,0.0178242,0.000267668,0.0001457032,0.001514176,0.7203874,0.0004338456,0.06541018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05485773,"threshold_uncertainty_score":0.1090769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03992281814024327,"score_gpt":0.2511352337116248,"score_spread":0.2112124155713815,"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."}}