{"id":"W7082249844","doi":"10.48448/y6ec-tk18","title":"Sensitive Content Classification in Social Media: A Holistic Resource and Evaluation","year":2025,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Moderation; Social media; Resource (disambiguation); Focus (optics); Content (measure theory); Open data","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":[0.01114152,0.00265702,0.001517996,0.00913159,0.001594923,0.003601869,0.002148048,0.002739907,0.002793224],"category_scores_gemma":[0.02417747,0.000362639,0.001785776,0.00383637,0.001263896,0.006666263,0.004219629,0.001888635,0.004372916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001623241,"about_ca_system_score_gemma":0.001598058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009844621,"about_ca_topic_score_gemma":0.01250183,"domain_scores_codex":[0.9879245,0.00544819,0.0009072773,0.00177899,0.003322457,0.0006186209],"domain_scores_gemma":[0.9825366,0.008597004,0.001060504,0.003915651,0.002698018,0.001192255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003425581,0.004395819,0.1192212,0.004975315,0.001564106,0.0009010217,0.001963616,0.02794222,0.02121998,0.006050296,0.2026541,0.6056867],"study_design_scores_gemma":[0.0004249381,0.003249546,0.1341291,0.001391047,0.001171911,0.00265555,0.006802346,0.6098099,0.04132143,0.01375651,0.18473,0.0005576343],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.655711,0.01593248,0.1146505,0.007039556,0.003099008,0.004907215,0.1278423,0.03361557,0.03720251],"genre_scores_gemma":[0.6140226,0.002802868,0.122541,0.001928666,0.001156202,0.002247052,0.2446403,0.001330383,0.009330974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01114152,"threshold_uncertainty_score":0.05892271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119768872665568,"score_gpt":0.322677729851037,"score_spread":0.2107008425844802,"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."}}