{"id":"W7008006905","doi":"","title":"ARCHIVEIT-279-WEEKLY-CSADDZ-20111213135808-00000-crawling208.us.archive.org-6683.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); 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":[0.001011786,0.002457384,0.001209899,0.007000523,0.002155894,0.005707704,0.002403147,0.001815117,0.8078671],"category_scores_gemma":[0.007490812,0.002063204,0.0008998407,0.009025912,0.0006447984,0.004030514,0.004006379,0.001423618,0.8986289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002904661,"about_ca_system_score_gemma":0.002035188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0547069,"about_ca_topic_score_gemma":0.07172185,"domain_scores_codex":[0.9991918,0.00007136788,0.00005514357,0.000161822,0.0003660943,0.0001537],"domain_scores_gemma":[0.9945999,0.0006228324,0.0002272005,0.001810906,0.001845636,0.0008935286],"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":[0.00002212564,0.00001107279,0.0001490593,0.00007874522,0.000003253376,0.000007415917,0.00003565882,0.00003190662,0.00009944831,0.0003851333,0.9887365,0.01043966],"study_design_scores_gemma":[0.00002824916,0.000006857244,0.001265673,0.00005427696,0.000003842305,0.00002859164,0.00003940205,0.0001490148,0.0006371586,0.0002658849,0.9975012,0.00001987416],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.000668463,0.0002301256,0.00274973,0.0005146791,0.0002229389,0.0001943135,0.5571119,0.1234857,0.3148222],"genre_scores_gemma":[0.003362037,0.0004398134,0.003678455,0.0003580629,0.0001120232,0.0002476977,0.4674034,0.08236545,0.4420331],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1921329,"threshold_uncertainty_score":0.2740543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009390905655486075,"score_gpt":0.1918931535615356,"score_spread":0.1825022479060495,"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."}}