{"id":"W7132997431","doi":"","title":"Torrential Twitter: Climate Change, Female Politicians, and Harassment","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Harassment; Categorization; Scale (ratio); Climate change; Democracy; Empirical research; Government (linguistics)","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":[0.001668211,0.0003144506,0.0002461653,0.001279694,0.006491916,0.004712644,0.000472518,0.001142782,0.009291511],"category_scores_gemma":[0.01241465,0.0002064884,0.0002320198,0.001544189,0.003384205,0.002750001,0.002293029,0.001651524,0.0009112044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003813767,"about_ca_system_score_gemma":0.002719172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1297794,"about_ca_topic_score_gemma":0.1747993,"domain_scores_codex":[0.9981193,0.0007905081,0.00005466259,0.0001332016,0.000490569,0.0004117326],"domain_scores_gemma":[0.9906251,0.003370043,0.003135298,0.0002963846,0.001113877,0.001459243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002230277,0.0002317189,0.5969118,0.000166023,0.00005644099,0.0005602685,0.3391255,0.00006994609,0.0007201592,0.005405342,0.01317288,0.04335682],"study_design_scores_gemma":[0.000008070772,0.00005112301,0.4670491,0.0001560475,0.00003072828,0.0001947776,0.5131214,0.000182094,0.0001697829,0.0009078719,0.01809989,0.00002896436],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952642,0.0005045453,0.0001777384,0.008556455,0.0001331585,0.00002515864,0.0001930637,0.000009842696,0.03775799],"genre_scores_gemma":[0.9945965,0.0004447569,0.00006628297,0.0008849181,0.00008921696,0.00002294876,0.00007987691,0.000009399399,0.003806082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1297794,"threshold_uncertainty_score":0.2580481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4198655359616368,"score_gpt":0.5343360000523788,"score_spread":0.114470464090742,"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."}}