{"id":"W4256389471","doi":"10.32920/ryerson.14638614","title":"The Local News Map : transparency, credibility, and critical cartography","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of British Columbia","funders":"","keywords":"Credibility; Transparency (behavior); Crowdsourcing; Journalism; Citizen journalism; Data science; Geography; Cartography; Political science; Computer science; Sociology; World Wide Web; Media studies","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.05356859,0.0006182648,0.0006411102,0.01712724,0.01434132,0.03147853,0.001740456,0.003057791,0.006580719],"category_scores_gemma":[0.1866694,0.0007070474,0.0003694065,0.01711595,0.05783016,0.01986151,0.01151302,0.003647686,0.0005392136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01699343,"about_ca_system_score_gemma":0.01520283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02986824,"about_ca_topic_score_gemma":0.0226344,"domain_scores_codex":[0.9524635,0.03747743,0.001273703,0.002144757,0.005629473,0.001011204],"domain_scores_gemma":[0.6616166,0.2869642,0.01417361,0.01835294,0.01552242,0.003370168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001003642,0.00002207158,0.00857033,0.0006497171,0.00003647425,0.0004097044,0.345998,0.001018219,0.0002325907,0.5722893,0.01579862,0.0548746],"study_design_scores_gemma":[0.00003771945,0.00003605072,0.009335076,0.002099433,0.00004595816,0.0002983722,0.2786243,0.002724243,0.0008021888,0.4738476,0.2320262,0.0001228338],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.208344,0.0113184,0.0942141,0.1882436,0.0017268,0.000756035,0.001683471,0.0007457982,0.4929677],"genre_scores_gemma":[0.9809318,0.001781243,0.0110429,0.001020495,0.0003198975,0.0002390891,0.0001614772,0.0001565373,0.004346528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05356859,"threshold_uncertainty_score":0.2833012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03473377274474258,"score_gpt":0.3297432201400526,"score_spread":0.29500944739531,"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."}}