{"id":"W7045103463","doi":"","title":"ARCHIVEIT-279-WEEKLY-IDLLHI-20120221135539-00000-crawling211.us.archive.org-6683.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":[0.0009547084,0.002474478,0.001195052,0.007083391,0.002118468,0.005592048,0.002361017,0.001707105,0.7777218],"category_scores_gemma":[0.007550546,0.002056983,0.0008851722,0.008775459,0.0006199979,0.004082199,0.00397974,0.001347306,0.8765047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002617545,"about_ca_system_score_gemma":0.001883891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05616857,"about_ca_topic_score_gemma":0.07218971,"domain_scores_codex":[0.9992211,0.00006682565,0.00005338792,0.000161499,0.0003491993,0.0001479492],"domain_scores_gemma":[0.9944564,0.0006411938,0.0002332807,0.001820486,0.001938018,0.0009105757],"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":[0.00002224628,0.00001031473,0.0001708676,0.00009295806,0.000003601382,0.000008406165,0.00004556042,0.00002770866,0.0001062687,0.000360649,0.9892476,0.009903858],"study_design_scores_gemma":[0.00002877164,0.000006977672,0.001528827,0.00006012741,0.000004511229,0.00003124436,0.00004295855,0.0001428521,0.0007018236,0.0002538939,0.9971774,0.00002066086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006781336,0.0002343071,0.002646856,0.0004537341,0.0002186573,0.0001951825,0.5814987,0.1282947,0.2857798],"genre_scores_gemma":[0.003631131,0.0004395622,0.003799685,0.0003630307,0.000128248,0.0002568079,0.4998321,0.09403986,0.3975096],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2222782,"threshold_uncertainty_score":0.3170529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007881875148422307,"score_gpt":0.1967216931081287,"score_spread":0.1888398179597064,"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."}}