{"id":"W2048941574","doi":"10.1007/s10502-012-9174-5","title":"Genre systems and “keeping track” in everyday life","year":2012,"lang":"en","type":"article","venue":"Archives and Museum Informatics","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research","keywords":"Ethnography; Everyday life; Perspective (graphical); Track (disk drive); Action (physics); Focus (optics); Sociology; Participant observation; Cultural heritage; Visual arts; Public relations; History; Computer science; Art; Political science; Social science; Anthropology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002291147,0.0002973849,0.0002301426,0.005921007,0.002518107,0.008960873,0.0007535147,0.0009164634,0.007630517],"category_scores_gemma":[0.01438331,0.0003000949,0.0003124228,0.006078101,0.005899047,0.008693655,0.002672738,0.001021601,0.0007253399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001825849,"about_ca_system_score_gemma":0.0009921574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008523189,"about_ca_topic_score_gemma":0.008959636,"domain_scores_codex":[0.997807,0.001062505,0.0001754796,0.0004360159,0.000361194,0.0001578206],"domain_scores_gemma":[0.9910079,0.003897607,0.001746351,0.00128732,0.00106988,0.0009910753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003542022,0.0001863763,0.2274078,0.0005522776,0.0001249343,0.0005357324,0.1942074,0.0007992628,0.003215408,0.3316792,0.007987848,0.2329497],"study_design_scores_gemma":[0.00005851832,0.0002601109,0.4656527,0.0004951681,0.000153687,0.001884006,0.1678411,0.004204853,0.001377714,0.2454942,0.1124047,0.0001732872],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7432734,0.005267198,0.02513032,0.005185772,0.000462278,0.00007357974,0.0007269155,0.0002629828,0.2196175],"genre_scores_gemma":[0.9903975,0.0004363483,0.005076469,0.000146413,0.0001052293,0.00002156893,0.000189559,0.00004912224,0.003577847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008960873,"threshold_uncertainty_score":0.02552664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02055123639676582,"score_gpt":0.2750988493591497,"score_spread":0.2545476129623839,"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."}}