{"id":"W7011649651","doi":"","title":"Metropolitics and metabolics: Rolling out environmentalism in Toronto","year":2006,"lang":"en","type":"other","venue":"EspaceINRS (National Institute for Scientific Research (Canada))","topic":"","field":"","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Environmentalism; Government (linguistics); Work (physics); State (computer science)","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"],"consensus_categories":[],"category_scores_codex":[0.004620411,0.0005954186,0.0006954346,0.00143537,0.0008337155,0.0006685052,0.001004631,0.0003321774,0.0005480567],"category_scores_gemma":[0.001111176,0.0006292367,0.0001134371,0.000796537,0.001857688,0.0005176694,0.0003812502,0.0006471185,0.00004916925],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01499793,"about_ca_system_score_gemma":0.0117619,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9782439,"about_ca_topic_score_gemma":0.999974,"domain_scores_codex":[0.9877856,0.0003109153,0.0006923467,0.001604681,0.007941717,0.001664688],"domain_scores_gemma":[0.9975161,0.0003467102,0.0003091321,0.0007460404,0.0005495802,0.0005324182],"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":[0.00002609492,0.0001091663,0.00009171284,0.0001188558,0.0001208886,0.00003027534,0.00004031563,0.001131287,0.0004266925,0.0955884,0.9021868,0.0001295195],"study_design_scores_gemma":[0.0009784914,0.00001970874,0.0002301703,0.0001320457,0.00002645272,0.000003788618,0.0002808152,0.002068351,0.0003767101,0.000784348,0.9945115,0.0005875829],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005743518,0.01034807,0.0003596766,0.003604978,0.006126008,0.004254125,0.02527892,0.0001389584,0.9493149],"genre_scores_gemma":[0.03190369,0.0001702529,0.004284451,0.00009278773,0.001321924,0.0005773726,0.005161865,0.0009315515,0.9555561],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09480405,"threshold_uncertainty_score":0.9996159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04321370646434212,"score_gpt":0.3357098510133849,"score_spread":0.2924961445490427,"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."}}