{"id":"W7017293599","doi":"","title":"ARCHIVEIT-2475-MONTHLY-NBVWAW-20111021052329-00001-crawling113.us.archive.org-6680.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":[0.001017241,0.001588975,0.001207118,0.005484541,0.001803688,0.005258624,0.002250776,0.001259377,0.850522],"category_scores_gemma":[0.007288328,0.001478238,0.0007636826,0.01177544,0.0005086792,0.002660021,0.002494857,0.001668298,0.9146901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003067891,"about_ca_system_score_gemma":0.002958619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1070848,"about_ca_topic_score_gemma":0.1206359,"domain_scores_codex":[0.9992527,0.00006998784,0.00005065163,0.0001430445,0.0003488066,0.0001348322],"domain_scores_gemma":[0.995663,0.0005777068,0.000194354,0.001173948,0.001772264,0.0006186909],"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":[0.00001387522,0.000008092181,0.0001129531,0.00006057439,0.000002412876,0.000003724003,0.00002069428,0.0000238039,0.0000407111,0.0003666824,0.9904813,0.008865112],"study_design_scores_gemma":[0.00002014904,0.000003118351,0.001322538,0.00005635868,0.000002823688,0.000009637824,0.00002951355,0.00006538021,0.0002464446,0.0003219996,0.9979109,0.00001117436],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0002717038,0.0001301476,0.0007905409,0.000382404,0.0001561928,0.00007872681,0.7696218,0.01614915,0.2124192],"genre_scores_gemma":[0.001922773,0.0004511487,0.002050068,0.000280166,0.00009301415,0.0002631004,0.5493172,0.02377338,0.421849],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.149478,"threshold_uncertainty_score":0.2132123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008832426600287706,"score_gpt":0.1898841934837717,"score_spread":0.181051766883484,"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."}}