{"id":"W2162525194","doi":"10.5204/mcj.220","title":"From TV to Twitter: How Ambient News Became Ambient Journalism","year":2010,"lang":"en","type":"article","venue":"M/C Journal","topic":"Public Relations and Crisis Communication","field":"Social Sciences","cited_by":242,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Citizen journalism; Journalism; Social media; News media; Media studies; China; Quake (natural phenomenon); Technical Journalism; Political science; Sociology; History; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004637625,0.0005104291,0.0002970941,0.002251216,0.006978507,0.01986756,0.0009816628,0.002502505,0.006874829],"category_scores_gemma":[0.009280833,0.000542186,0.0006310564,0.00201447,0.01034595,0.02188191,0.01024118,0.003622188,0.001981417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001927268,"about_ca_system_score_gemma":0.001196497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0023401,"about_ca_topic_score_gemma":0.003885375,"domain_scores_codex":[0.9950093,0.003210621,0.0001898223,0.0005281237,0.0006613134,0.0004009535],"domain_scores_gemma":[0.9940622,0.003816445,0.0003328753,0.0005564112,0.0005447403,0.0006872956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002999617,0.0001609095,0.01219437,0.0007102892,0.00008041868,0.003426008,0.5865932,0.000450308,0.004789316,0.2197102,0.03945578,0.1321293],"study_design_scores_gemma":[0.00006211193,0.000134295,0.005034147,0.000496808,0.00005973667,0.0007959939,0.1331115,0.001097122,0.001966105,0.05220225,0.8049266,0.000113404],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2963838,0.009444511,0.04034314,0.06492104,0.006650502,0.0002767453,0.0006634228,0.001348068,0.5799688],"genre_scores_gemma":[0.9507173,0.003551722,0.00625863,0.006002626,0.002229892,0.0002124484,0.0002714876,0.0006555254,0.03010046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01986756,"threshold_uncertainty_score":0.02452642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0300186511368465,"score_gpt":0.3235255061224732,"score_spread":0.2935068549856267,"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."}}