{"id":"W7017450981","doi":"","title":"ARCHIVEIT-2475-MONTHLY-PCMWBL-20111221073748-00001-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); 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":[0.000835105,0.001787412,0.001122584,0.005970836,0.001795976,0.005375964,0.00222199,0.001287132,0.8846473],"category_scores_gemma":[0.006258427,0.001429515,0.0007811327,0.01099209,0.0005289692,0.002940097,0.002978054,0.00135676,0.9319313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002377426,"about_ca_system_score_gemma":0.002167366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0707156,"about_ca_topic_score_gemma":0.07608523,"domain_scores_codex":[0.9993441,0.00005504645,0.00003976101,0.0001190841,0.0003189743,0.0001229738],"domain_scores_gemma":[0.9955967,0.0005649703,0.0001874856,0.001098324,0.001847384,0.0007050766],"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":[0.00001673535,0.000008908624,0.0001225515,0.00006546696,0.000002262421,0.00000535048,0.00002587739,0.00002518828,0.00005424137,0.0003189311,0.9861491,0.01320551],"study_design_scores_gemma":[0.0000162075,0.00000333209,0.0008963252,0.00004940863,0.000002339955,0.00001256573,0.00002741583,0.00005757431,0.0002577584,0.0002427006,0.9984229,0.00001158112],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003809436,0.0001799238,0.001552883,0.0003705545,0.0002046075,0.0001235214,0.5742484,0.04374905,0.3791903],"genre_scores_gemma":[0.002169211,0.0004138364,0.002629568,0.0003354665,0.0001162416,0.0002138089,0.39301,0.04455488,0.5565569],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1153527,"threshold_uncertainty_score":0.1645366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008829769469260488,"score_gpt":0.1898481613720556,"score_spread":0.1810183919027951,"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."}}