{"id":"W1529203432","doi":"","title":"Environment and Energy Policy: Comparing Reports from US and Canadian Television News","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Political science; Granger causality; Energy (signal processing); News media; Geography; Meteorology; Econometrics; Economics; Statistics; Law; Mathematics","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":[0.003186013,0.000370112,0.0003208377,0.01332905,0.002849607,0.005504657,0.0009268745,0.0004773251,0.004880438],"category_scores_gemma":[0.03171713,0.0002760115,0.0003221019,0.02605272,0.001088135,0.001204707,0.001676619,0.0006191829,0.0003935746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02337418,"about_ca_system_score_gemma":0.01914739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9707696,"about_ca_topic_score_gemma":0.9681261,"domain_scores_codex":[0.9953594,0.000500015,0.0001725896,0.0002194767,0.002962105,0.0007864014],"domain_scores_gemma":[0.9707724,0.00915545,0.005578388,0.0005954348,0.01264,0.001258441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004180695,0.000121625,0.8409645,0.0007186646,0.0003346658,0.0003915421,0.06878022,0.0008320881,0.001042812,0.004071512,0.01670708,0.06561717],"study_design_scores_gemma":[0.000006810142,0.00002046825,0.9487668,0.0001252113,0.000072347,0.000034346,0.03245223,0.0002376663,0.0003037898,0.00008477586,0.01786003,0.00003560061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9185554,0.002266099,0.0001909813,0.002194853,0.00006610101,0.00009159152,0.01445101,0.00004878024,0.06213516],"genre_scores_gemma":[0.9845426,0.002801734,0.0002167889,0.000229677,0.00005993397,0.00004369472,0.007284253,0.0000305114,0.004790767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02923036,"threshold_uncertainty_score":0.1695924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08706926273659532,"score_gpt":0.3378662670935479,"score_spread":0.2507970043569526,"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."}}