{"id":"W3200612959","doi":"10.22148/001c.28215","title":"Celebrating 5 Years of Cultural Analytics","year":2021,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytics; Data science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02752611,0.001541668,0.001215783,0.004668015,0.007166639,0.02581575,0.002704576,0.006066264,0.02866604],"category_scores_gemma":[0.06584215,0.0005737618,0.001451043,0.00432027,0.008248025,0.02597242,0.02198895,0.01706745,0.01509733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003316294,"about_ca_system_score_gemma":0.007825942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005028865,"about_ca_topic_score_gemma":0.01347317,"domain_scores_codex":[0.9860163,0.003460262,0.0004848726,0.001393633,0.006678534,0.001966353],"domain_scores_gemma":[0.9238806,0.0156087,0.002308499,0.007773664,0.02127617,0.0291523],"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":[0.00008346708,0.00004787999,0.0009359408,0.0002004422,0.00003532039,0.00009235714,0.001682433,0.0001003444,0.0003651994,0.03859481,0.8963128,0.06154895],"study_design_scores_gemma":[0.000006627482,0.00003046764,0.0009229208,0.0002935917,0.00001115653,0.00009129355,0.001731806,0.0002179087,0.0002450444,0.023135,0.9732758,0.00003837341],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.006080994,0.03918023,0.0212029,0.7088255,0.1708466,0.00009843412,0.002765722,0.001917067,0.04908252],"genre_scores_gemma":[0.1279632,0.055887,0.06415594,0.2927245,0.1947554,0.0005254011,0.0109031,0.005293807,0.2477917],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.02866604,"threshold_uncertainty_score":0.1455737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06948626028111493,"score_gpt":0.3942367134171539,"score_spread":0.324750453136039,"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."}}