{"id":"W6980004544","doi":"","title":"ARCHIVEIT-2901-MONTHLY-EWDNWK-20120210092317-00006-crawling208.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":"Identification (biology); Process (computing); Product (mathematics); Work (physics)","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":[],"category_scores_codex":[0.000944652,0.002353759,0.001329599,0.007620038,0.001811328,0.005572403,0.002273815,0.001473213,0.8053883],"category_scores_gemma":[0.007742902,0.001689526,0.000937011,0.01160694,0.0005413928,0.003289516,0.003161511,0.001366712,0.9090496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00223896,"about_ca_system_score_gemma":0.002221207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05916666,"about_ca_topic_score_gemma":0.06886896,"domain_scores_codex":[0.999184,0.00006600871,0.00005130913,0.0001630993,0.0003930112,0.0001425084],"domain_scores_gemma":[0.9947268,0.0006371975,0.0001969433,0.001466626,0.002191277,0.0007810913],"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":[0.0000193301,0.00001028851,0.000135016,0.0000692715,0.000003058353,0.000005578964,0.0000250539,0.00002747021,0.00006704401,0.0003062731,0.988257,0.01107459],"study_design_scores_gemma":[0.00002372525,0.000005111605,0.001150741,0.00005704379,0.000003760448,0.00002063876,0.00002935786,0.0001180293,0.0004285175,0.000354949,0.9977919,0.00001618407],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0004593419,0.0001990794,0.002092199,0.000379994,0.0001663615,0.0001397446,0.6406522,0.08038209,0.275529],"genre_scores_gemma":[0.002338409,0.0004198987,0.003463924,0.0003068318,0.0001048449,0.0002145281,0.5584786,0.06426366,0.3704092],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1946117,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007531703411791824,"score_gpt":0.1957574702490759,"score_spread":0.188225766837284,"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."}}