{"id":"W4229965010","doi":"10.32920/ryerson.14657859","title":"Reading the rebate: information at the edges of 20th century photographs","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Photography and Visual Culture","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Photography; Reading (process); Visual arts; Character (mathematics); The arts; Art; Computer science; Political science; Law","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":[0.001983238,0.0002491066,0.0001740989,0.002761876,0.003896432,0.00567898,0.0004959967,0.0005571144,0.01472766],"category_scores_gemma":[0.005653766,0.0002688351,0.0001559068,0.002655497,0.005816625,0.005790562,0.003683554,0.001265837,0.001566173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002825563,"about_ca_system_score_gemma":0.0010822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006935852,"about_ca_topic_score_gemma":0.02512891,"domain_scores_codex":[0.9986922,0.0006389931,0.00004072355,0.0001372124,0.0003664376,0.0001244885],"domain_scores_gemma":[0.9971129,0.001464245,0.0003826994,0.0005176888,0.0003637674,0.0001587219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001291159,0.00002119388,0.005491453,0.0003741101,0.00001343542,0.001543211,0.6290863,0.0001820832,0.005711275,0.09473605,0.04251458,0.2201972],"study_design_scores_gemma":[0.000004451606,0.00002276541,0.01439019,0.0005544482,0.000008419105,0.000881603,0.1217974,0.0000735233,0.001991889,0.004957724,0.8552965,0.00002110286],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3050937,0.01272969,0.009115417,0.01457693,0.0009201021,0.00006673027,0.0005526273,0.0003694618,0.6565752],"genre_scores_gemma":[0.8698887,0.005488275,0.008486443,0.000949396,0.000486458,0.00002776629,0.0002326457,0.0003373685,0.114103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01472766,"threshold_uncertainty_score":0.0492689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02826207798377502,"score_gpt":0.2443889397537145,"score_spread":0.2161268617699395,"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."}}