{"id":"W6950171976","doi":"10.5281/zenodo.8204346","title":"The Local News Data Hub: Championing data journalism and equity, one story at a time","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Journalism; Census; Metropolitan area; Population; Inequality; The Internet; Economic inequality; Population statistics; Gini coefficient","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":["sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01198348,0.0001139309,0.0001529169,0.0002893009,0.005763659,0.002606117,0.004901939,0.00005361247,0.002588454],"category_scores_gemma":[0.004237768,0.00008724148,0.00002600935,0.001191765,0.0003482215,0.0007482392,0.01790703,0.0003009436,0.01428339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005622792,"about_ca_system_score_gemma":0.000008363861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002340303,"about_ca_topic_score_gemma":0.000007915295,"domain_scores_codex":[0.9961911,0.000809345,0.000410756,0.0007371696,0.00146116,0.0003904602],"domain_scores_gemma":[0.9964744,0.0004330324,0.0002039003,0.002214255,0.000472611,0.0002018146],"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":[0.000038491,0.0000204491,0.000006048479,0.00000549162,0.00002464098,0.000007210203,0.0006180115,0.0001700129,0.0005862831,0.001033364,0.5111199,0.4863701],"study_design_scores_gemma":[0.0002496358,0.0000525939,0.0005615785,0.0000202782,0.00001266231,0.00005709629,0.001287854,0.1112753,0.000006593302,0.00179934,0.8845706,0.0001064636],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3237767,0.004731175,0.2233073,0.1217194,0.002190571,0.003091352,0.007577341,0.007103804,0.3065024],"genre_scores_gemma":[0.9672245,0.003314363,0.000510764,0.0005917173,0.0005040172,7.179832e-8,0.011389,0.001387623,0.0150779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6434478,"threshold_uncertainty_score":0.9984293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3969140162433996,"score_gpt":0.4001568897488385,"score_spread":0.003242873505438892,"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."}}