{"id":"W3004383240","doi":"10.22148/001c.11822","title":"Other people's data: humanities edition","year":2016,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital humanities; Process (computing); Raw data; Resource (disambiguation); Computer science; Digital curation; World Wide Web; Data 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":["open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0039849,0.001030457,0.0009125128,0.01021376,0.001817749,0.009727487,0.001503561,0.001412772,0.4502846],"category_scores_gemma":[0.02380534,0.001150141,0.0007239881,0.02400159,0.00100213,0.007855253,0.004639787,0.003949496,0.4651349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001556934,"about_ca_system_score_gemma":0.004432084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008943743,"about_ca_topic_score_gemma":0.01376226,"domain_scores_codex":[0.9973752,0.0003779129,0.0004474633,0.0003760247,0.001163379,0.0002600049],"domain_scores_gemma":[0.9833535,0.004518004,0.0007890317,0.006046094,0.004245697,0.001047745],"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":[0.0000307115,0.000009345011,0.0001944771,0.0001914266,0.000004704513,0.0000238778,0.0001678099,0.00002096994,0.0001125182,0.002941671,0.9792915,0.0170111],"study_design_scores_gemma":[0.000005683538,0.000001537717,0.0003404157,0.00009675915,0.000001370416,0.00001898669,0.00008367803,0.00001060827,0.00008628964,0.001078138,0.9982702,0.000006357252],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0004472275,0.0008262706,0.002617659,0.002914389,0.002968191,0.0001560276,0.7820673,0.007533521,0.2004693],"genre_scores_gemma":[0.006457399,0.002542282,0.01023317,0.002846285,0.001381015,0.001180205,0.7057104,0.01471922,0.2549302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9984964,"threshold_uncertainty_score":0.7841023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1393494022932569,"score_gpt":0.2780875505455687,"score_spread":0.1387381482523118,"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."}}