{"id":"W1832677924","doi":"","title":"A bit of data regarding energy in Eastern Canada (Mousseau)","year":2014,"lang":"en","type":"article","venue":"","topic":"Coal and Coke Industries Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy (signal processing); Electricity; Bit (key); Production (economics); Nothing; Primary energy; Business; Economics; Engineering; Computer science; Statistics; Computer security; Mathematics; Electrical 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":[],"consensus_categories":[],"category_scores_codex":[0.0005775806,0.0005387196,0.0005314413,0.009351242,0.001987681,0.002221089,0.0007224019,0.0004807759,0.01733079],"category_scores_gemma":[0.003059457,0.0002299717,0.0006321661,0.03330806,0.0004526799,0.0007910836,0.0008072646,0.0006687638,0.002351477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01768993,"about_ca_system_score_gemma":0.05135716,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.99138,"about_ca_topic_score_gemma":0.9955657,"domain_scores_codex":[0.9983,0.00005235106,0.000105793,0.0001286111,0.001056167,0.0003570298],"domain_scores_gemma":[0.9941923,0.0003839486,0.0003394838,0.0001637321,0.00454607,0.0003745413],"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":[0.0001891973,0.00003198697,0.07770357,0.004024155,0.00026876,0.0004124202,0.0009696336,0.001045928,0.0009279065,0.007203816,0.7084463,0.1987763],"study_design_scores_gemma":[0.000005607752,0.00001807322,0.3022986,0.001164085,0.00007868009,0.0001087804,0.0008382536,0.00008978309,0.0004536553,0.0002764751,0.6946217,0.00004633549],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.05271646,0.1500321,0.001471631,0.02281589,0.002634483,0.0001715979,0.5228083,0.0005248085,0.2468248],"genre_scores_gemma":[0.2654766,0.1926196,0.004184016,0.01173282,0.001140084,0.0002098348,0.3129173,0.0005010939,0.2112187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01768993,"threshold_uncertainty_score":0.12835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06273004242346462,"score_gpt":0.277447225056337,"score_spread":0.2147171826328723,"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."}}