{"id":"W1603468035","doi":"10.7202/1025147ar","title":"Archives and Technological Selection","year":2014,"lang":"en","type":"article","venue":"Cinémas Revue d études cinématographiques","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digitization; Plan (archaeology); Selection (genetic algorithm); Monopoly; Digital Archives; Order (exchange); Politics; Emerging technologies; Search engine indexing; History; Library science; Computer science; World Wide Web; Political science; Law; Telecommunications; Archaeology; Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009620396,0.0001805357,0.000198019,0.000301807,0.0002525353,0.000211659,0.0001480763,0.00002204278,0.00006944845],"category_scores_gemma":[0.00002559629,0.0001502129,0.00009556788,0.00007238404,0.0007255291,0.0002390183,0.00008264334,0.0001362859,0.00002019177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000044169,"about_ca_system_score_gemma":0.00000390276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001061183,"about_ca_topic_score_gemma":0.00006654293,"domain_scores_codex":[0.9991193,0.00004615431,0.0002070902,0.0003117963,0.00009624263,0.0002194319],"domain_scores_gemma":[0.9995709,0.0001281605,0.00006751576,0.0001318742,0.00002234921,0.00007921264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001187178,0.00009123187,0.0009255844,0.00007727481,0.00004323548,0.000002038994,0.0005984165,0.000001921586,0.00006250459,0.9563484,0.0002431608,0.04159442],"study_design_scores_gemma":[0.0001479982,0.0002156103,0.01664886,0.00008227219,0.00002516258,0.00001878104,0.0001905709,0.0003549403,0.0001060646,0.1716075,0.8103619,0.0002403813],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1443598,0.00004631894,0.0008739759,0.001207857,0.00008012729,0.0001936695,0.00000989464,0.000513136,0.8527153],"genre_scores_gemma":[0.9965922,0.0001305601,0.0007162998,0.0003587521,0.0002670672,0.00005491514,0.00002477512,0.00001859397,0.001836794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8522325,"threshold_uncertainty_score":0.6125506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02193525825774988,"score_gpt":0.2000720387839041,"score_spread":0.1781367805261542,"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."}}