{"id":"W7036015876","doi":"","title":"ARCHIVEIT-3490-TWELVE_HOURS-WHDYJE-20130122153518-00000-crawling113.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":[0.001086746,0.002426216,0.001522219,0.00797912,0.00230618,0.006695359,0.002708656,0.001572391,0.8514685],"category_scores_gemma":[0.008887285,0.001929385,0.001110654,0.01164875,0.0007004888,0.004128389,0.004398778,0.001459506,0.9322195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002408732,"about_ca_system_score_gemma":0.002517004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05935916,"about_ca_topic_score_gemma":0.06873497,"domain_scores_codex":[0.9991014,0.00007423273,0.00005769745,0.0001786892,0.0004373494,0.0001506825],"domain_scores_gemma":[0.9939154,0.0007412214,0.0001988093,0.001741008,0.002575718,0.0008278473],"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":[0.00002190491,0.000009416216,0.0001116604,0.00008312694,0.000003417859,0.000007084352,0.00003806464,0.00002196241,0.00007903261,0.0002721929,0.9873002,0.01205188],"study_design_scores_gemma":[0.00002061127,0.000004990217,0.0008322064,0.00005947161,0.000003740053,0.00002109794,0.00004457864,0.00006914247,0.0004304935,0.0002900291,0.9982065,0.00001709335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0004544535,0.000244767,0.002707467,0.0004472909,0.000283647,0.0001912718,0.5437118,0.1073498,0.3446095],"genre_scores_gemma":[0.002225684,0.0004824668,0.004339723,0.0003482227,0.0001210627,0.0002533663,0.4477523,0.08978815,0.454689],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1485315,"threshold_uncertainty_score":0.2118621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006848667044617359,"score_gpt":0.1934217766070248,"score_spread":0.1865731095624074,"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."}}