{"id":"W4241286520","doi":"10.32920/ryerson.14638218","title":"The Missing News: Filters and Blind Spots in Canada's Press","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blind spot; History; Art history; Political science; Computer science; Artificial intelligence","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":[0.006005317,0.0009856087,0.001228117,0.01617414,0.009311362,0.0221726,0.002142475,0.003282117,0.01712845],"category_scores_gemma":[0.02377789,0.0008239869,0.0003985954,0.02754827,0.01273798,0.008610532,0.002320015,0.004114051,0.003404803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07490487,"about_ca_system_score_gemma":0.121275,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9369656,"about_ca_topic_score_gemma":0.9583033,"domain_scores_codex":[0.9925154,0.0008772897,0.0002779951,0.0003490395,0.004672995,0.001307183],"domain_scores_gemma":[0.9673227,0.007902692,0.001320265,0.001043092,0.01981013,0.002601114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000693599,0.00001161961,0.0009868601,0.001177112,0.00003847529,0.0001642493,0.004027814,0.000216608,0.0001357392,0.1059809,0.7402261,0.1469652],"study_design_scores_gemma":[0.000009922092,0.000006233775,0.005470319,0.002283689,0.00003092131,0.00009220732,0.003431688,0.00009174375,0.0002123411,0.01035324,0.9779727,0.00004502697],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.002708158,0.7830326,0.0009253222,0.1192326,0.005085355,0.00002449049,0.001582799,0.0001670023,0.0872417],"genre_scores_gemma":[0.1496487,0.7437214,0.001585225,0.02469981,0.007237497,0.00004956851,0.001688573,0.000463162,0.07090602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07490487,"threshold_uncertainty_score":0.5434754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05799593769679588,"score_gpt":0.3148440767460268,"score_spread":0.2568481390492309,"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."}}