{"id":"W6979996401","doi":"","title":"ARCHIVEIT-279-WEEKLY-XWWUNR-20120925135637-00000-crawling113.us.archive.org-6681.warc.gz","year":2012,"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); Work (physics); 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":[0.001052259,0.002364347,0.001226233,0.006783131,0.002080574,0.005811223,0.002349282,0.001718625,0.822421],"category_scores_gemma":[0.00817395,0.001955465,0.0009210799,0.008199935,0.0006336334,0.004054463,0.00408352,0.001355143,0.903837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002572808,"about_ca_system_score_gemma":0.001849282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05113246,"about_ca_topic_score_gemma":0.06580689,"domain_scores_codex":[0.9991223,0.00007748219,0.00005793504,0.0001835898,0.0003987086,0.000159979],"domain_scores_gemma":[0.9942359,0.0006412456,0.0002262804,0.001959765,0.00199556,0.0009412162],"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":[0.00002162838,0.00001119858,0.0001581516,0.00007901229,0.000003482245,0.000007732965,0.00004059284,0.00002890504,0.0001059256,0.0003632713,0.9874353,0.01174467],"study_design_scores_gemma":[0.00002688531,0.000007378548,0.00130302,0.00005491731,0.000004091729,0.00002901622,0.00003970012,0.0001537145,0.0006508867,0.0002568167,0.9974541,0.00001956595],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0007065384,0.0002260098,0.003136296,0.0005266512,0.000247439,0.0002257461,0.4884339,0.1515103,0.3549871],"genre_scores_gemma":[0.003567066,0.0004005236,0.003927464,0.0003799105,0.0001266464,0.0002538056,0.3965575,0.09659865,0.4981884],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.177579,"threshold_uncertainty_score":0.2532949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008018582169310048,"score_gpt":0.1971476557881278,"score_spread":0.1891290736188178,"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."}}