{"id":"W7131071099","doi":"10.25549/garland-ouc11399n4o8","title":"Louis J. Persky, letter, 1936-01-11, to I.L. Raymond","year":2021,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); East Asia; St louis; SAINT","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009785854,0.0008733532,0.0009284026,0.002397374,0.001625799,0.003709802,0.0009772629,0.001628776,0.3463475],"category_scores_gemma":[0.008573095,0.0005730863,0.0003714938,0.006841846,0.0003079582,0.00277139,0.001412101,0.001795315,0.4195963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771037,"about_ca_system_score_gemma":0.002512841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06348085,"about_ca_topic_score_gemma":0.1210026,"domain_scores_codex":[0.9993232,0.00009318953,0.00007139361,0.0001680061,0.0002278975,0.0001163307],"domain_scores_gemma":[0.9973719,0.0008538489,0.0002341242,0.0001974056,0.001028811,0.0003138514],"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":[0.000006618902,9.498447e-7,0.00008572095,0.00001536732,5.625348e-7,0.000002284131,0.000004459713,0.000003105778,0.000002212273,0.00007018507,0.9991449,0.0006636379],"study_design_scores_gemma":[0.00002009601,0.000003107911,0.001205412,0.00007083867,0.000001732312,0.00000752523,0.0001131103,0.00002683591,0.00002619959,0.0001958942,0.9983227,0.000006477831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003966975,0.001022609,0.000160766,0.007122862,0.0008793589,0.00003261457,0.949874,0.0007021422,0.0398089],"genre_scores_gemma":[0.003471787,0.00249121,0.0004580697,0.005663591,0.0003754724,0.0002980642,0.7784101,0.000989817,0.2078419],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3463475,"threshold_uncertainty_score":0.9323559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007476292557392906,"score_gpt":0.1655941439220273,"score_spread":0.1581178513646344,"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."}}