{"id":"W7017270354","doi":"","title":"ARCHIVEIT-2475-MONTHLY-XIRTZH-20110720170920-00000-crawling209.us.archive.org-6681.warc.gz","year":2011,"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":[0.0008328128,0.002026729,0.001150809,0.006553496,0.001671314,0.00493003,0.002115939,0.001178111,0.8329422],"category_scores_gemma":[0.005595369,0.001473225,0.0008381516,0.01108915,0.0004994836,0.002657901,0.002920817,0.00127569,0.9061114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002091383,"about_ca_system_score_gemma":0.002135894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07219011,"about_ca_topic_score_gemma":0.07503892,"domain_scores_codex":[0.9993778,0.00005340383,0.00003977586,0.0001212367,0.000284656,0.0001230938],"domain_scores_gemma":[0.9961666,0.0005013181,0.0001539067,0.001018505,0.001601942,0.0005575864],"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":[0.0000192422,0.00000798348,0.0001335763,0.00007675796,0.000002905425,0.000005458515,0.00002955394,0.000026586,0.00006445227,0.000303568,0.9884271,0.01090268],"study_design_scores_gemma":[0.00002033913,0.000003669554,0.001168823,0.00005841407,0.000003319209,0.00001382271,0.00003246485,0.00007477752,0.0003386269,0.0002865266,0.9979856,0.00001360416],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003508043,0.0001634894,0.001367783,0.0002759828,0.0001491789,0.0001010297,0.7349726,0.04233025,0.2202889],"genre_scores_gemma":[0.002091795,0.000419611,0.002717493,0.0002477524,0.00009707129,0.0001954432,0.614548,0.04332032,0.3363623],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1670578,"threshold_uncertainty_score":0.2382877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009096537559697235,"score_gpt":0.1914832801230226,"score_spread":0.1823867425633253,"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."}}