{"id":"W7026491463","doi":"","title":"ARCHIVEIT-3490-PATCH-FTCQWR-20130129204153-00000-wbgrp-crawl065.us.archive.org-6681.warc.gz","year":2013,"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":[0.0009487536,0.002217601,0.001340619,0.006133047,0.002237507,0.006085119,0.003159629,0.001717488,0.8895824],"category_scores_gemma":[0.007819276,0.002008514,0.001001219,0.008808348,0.0007348572,0.004455091,0.004098641,0.001549498,0.9413888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002931375,"about_ca_system_score_gemma":0.002143997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07596957,"about_ca_topic_score_gemma":0.07127465,"domain_scores_codex":[0.9992622,0.00005751537,0.00004080131,0.0001395714,0.0003508146,0.0001490553],"domain_scores_gemma":[0.9944152,0.0007170988,0.0001900828,0.001668203,0.002254582,0.0007549673],"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":[0.00002190894,0.000009671127,0.00009613677,0.00007591995,0.000002540598,0.000006847863,0.00005052335,0.00002198513,0.00006413386,0.0003179933,0.9888108,0.01052137],"study_design_scores_gemma":[0.00001737103,0.000003776451,0.0005855634,0.00005373142,0.000002862004,0.00001611177,0.00003870964,0.00004213986,0.0003294379,0.0002476535,0.9986486,0.00001404996],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003954657,0.0002021005,0.002459299,0.0003841984,0.0002893117,0.0001435003,0.4614876,0.09419459,0.440444],"genre_scores_gemma":[0.002445714,0.0003806196,0.002827113,0.0004063295,0.0001305535,0.000204471,0.3139029,0.1119839,0.5677183],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1104176,"threshold_uncertainty_score":0.1574972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006328401612985496,"score_gpt":0.1888563322471583,"score_spread":0.1825279306341728,"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."}}