{"id":"W6945564693","doi":"10.25549/pcra-c14-135394","title":"Wigglesworth letters, 1924-1949","year":2013,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Brother; Government (linguistics); Table (database); Key (lock); Character (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00002319546,0.0002544034,0.0002655755,0.00005518608,0.000109485,0.0001066167,0.0006974592,0.0001882844,0.4526286],"category_scores_gemma":[0.000009887322,0.0002317374,0.0001929312,0.0001790003,0.0004642543,0.0003774865,0.0008223097,0.0001983504,0.262999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001284776,"about_ca_system_score_gemma":0.00001763691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004015478,"about_ca_topic_score_gemma":0.00005062203,"domain_scores_codex":[0.9988366,0.00002240078,0.0001664989,0.000347219,0.0003433565,0.0002838617],"domain_scores_gemma":[0.9991718,0.00003321535,0.0002083439,0.0003891137,0.000005071453,0.0001924763],"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":[0.00002172141,0.00008819699,0.003577152,0.00002930749,0.00002175573,0.00003271292,0.00001514063,0.000001851398,0.000009095736,9.854205e-7,0.9958794,0.0003227226],"study_design_scores_gemma":[0.0001985509,0.00001597316,0.0002100706,0.00002411577,0.00002775956,0.000003544979,0.001078238,0.0000014571,0.000005587779,0.00001855609,0.9981345,0.000281648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004639925,0.00001729819,0.000006467225,0.000441032,0.00003973763,0.0001460481,0.986491,0.00007290201,0.008145589],"genre_scores_gemma":[0.0002373312,0.00006681391,0.0000232951,0.000354666,0.00003747597,2.906753e-7,0.9971787,0.00001925999,0.002082191],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1896296,"threshold_uncertainty_score":0.9449975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008026502856511965,"score_gpt":0.1490689399036275,"score_spread":0.1410424370471156,"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."}}