{"id":"W7008183750","doi":"","title":"ARCHIVEIT-3490-DAILY-NWQXQD-20130203073732-00000-wbgrp-crawl062.us.archive.org-6680.warc.gz","year":2013,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Identification (biology); Product (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001010944,0.002130832,0.001296165,0.006887717,0.002320657,0.007080933,0.002787595,0.001483773,0.8593879],"category_scores_gemma":[0.007442495,0.00179524,0.0009811929,0.0109329,0.0007292375,0.003953422,0.003718865,0.001525,0.9270939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003414615,"about_ca_system_score_gemma":0.002975871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09911186,"about_ca_topic_score_gemma":0.09605731,"domain_scores_codex":[0.9991899,0.00006268346,0.00004908183,0.0001426377,0.0004082207,0.0001475278],"domain_scores_gemma":[0.9945391,0.0005630278,0.0001895948,0.001365108,0.002603059,0.0007401225],"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":[0.00002351757,0.000009883035,0.0001253799,0.00008384675,0.000003016818,0.000007010794,0.00004810145,0.00002836831,0.00007240468,0.0004375018,0.986643,0.01251803],"study_design_scores_gemma":[0.00001414486,0.000003104375,0.0006400335,0.00004518366,0.000002501592,0.00001348659,0.00003587176,0.00003843134,0.0002844321,0.0002276207,0.9986821,0.0000131543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0004133394,0.0002271258,0.001984017,0.0003766509,0.0002871249,0.0001322185,0.5212822,0.06034568,0.4149517],"genre_scores_gemma":[0.002121667,0.0004402472,0.002741067,0.0003259489,0.0001134158,0.0001849863,0.339712,0.06310878,0.5912519],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1406121,"threshold_uncertainty_score":0.2005661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006363178989004297,"score_gpt":0.1879554218852177,"score_spread":0.1815922428962134,"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."}}