{"id":"W2005853706","doi":"10.1080/10807030902761312","title":"Web Information and Social Impacts of Disasters in China","year":2009,"lang":"en","type":"article","venue":"Human and Ecological Risk Assessment An International Journal","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Social Science Fund of China; National Office for Philosophy and Social Sciences; National Natural Science Foundation of China","keywords":"China; Web application; Business; Social media; World Wide Web; Computer science; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006572048,0.00005890073,0.00009508874,0.0001383797,0.0003123863,0.0003137292,0.0001798514,0.00004633832,0.0001264297],"category_scores_gemma":[0.00003661697,0.00004610154,0.00002703718,0.00004826715,0.0001431023,0.001284435,0.00003837192,0.0001581078,0.000001131038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006485115,"about_ca_system_score_gemma":0.00003490942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000591125,"about_ca_topic_score_gemma":0.0005199897,"domain_scores_codex":[0.999121,0.0001184039,0.0002382192,0.00007176543,0.000310759,0.0001398721],"domain_scores_gemma":[0.9996457,0.00002113848,0.0001936222,0.00002233904,0.00004798036,0.00006928582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006043438,0.0003921121,0.7996908,0.000004961201,0.00002967473,0.00001356175,0.01925011,0.00002697062,0.0001629245,0.1103158,0.0004103977,0.06964223],"study_design_scores_gemma":[0.0005397811,0.0002011068,0.9802486,0.000009311414,0.000005572309,0.000001709855,0.005974181,0.0002186878,6.173599e-7,0.01104481,0.001697337,0.00005831604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982051,0.000006725214,0.00004265252,0.001356002,0.0001338116,0.00006825443,0.00000334732,0.000007575126,0.01633066],"genre_scores_gemma":[0.9990821,0.0003865404,0.0001710774,0.0001598812,0.0001396892,9.201954e-7,0.000005889013,9.485018e-7,0.00005296622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1805577,"threshold_uncertainty_score":0.3025298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01555115084899188,"score_gpt":0.3585653515791639,"score_spread":0.343014200730172,"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."}}