{"id":"W6989451859","doi":"","title":"ARCHIVEIT-2475-NONE-YRJFLK-20111223191715-00005-crawling206.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":[0.0009302358,0.002118673,0.001361575,0.007642958,0.002333728,0.006296307,0.002799787,0.001633117,0.8870426],"category_scores_gemma":[0.007596805,0.001702459,0.0008851899,0.01252088,0.0006720844,0.003746122,0.003937699,0.001444525,0.9404129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002653339,"about_ca_system_score_gemma":0.002663341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08493874,"about_ca_topic_score_gemma":0.08552198,"domain_scores_codex":[0.9992279,0.00006781163,0.00005099114,0.0001491332,0.000357685,0.0001465406],"domain_scores_gemma":[0.994164,0.0008036424,0.0002113753,0.001452557,0.002604362,0.0007639545],"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":[0.00001798213,0.000007809841,0.0001095355,0.00009845434,0.000002518535,0.000006667401,0.00004329606,0.00001930797,0.00006318594,0.0003171187,0.9877496,0.01156445],"study_design_scores_gemma":[0.00001536315,0.000002892498,0.0006723133,0.00006865694,0.000002655824,0.00001576463,0.00004283791,0.00004077589,0.0002441027,0.0002527156,0.9986289,0.00001295018],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0002903325,0.0002066835,0.001592902,0.0003621699,0.0002193841,0.0001289065,0.6468244,0.04510298,0.3052723],"genre_scores_gemma":[0.001846623,0.0004557837,0.002926808,0.0003504256,0.00009969667,0.0002175734,0.5028602,0.05153244,0.4397104],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1129574,"threshold_uncertainty_score":0.1688887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009183023362623978,"score_gpt":0.1923325129161312,"score_spread":0.1831494895535072,"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."}}