{"id":"W6989319822","doi":"","title":"ARCHIVEIT-2901-BIMONTHLY-BIOLDT-20120924162106-00000-crawling211.us.archive.org-6680.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":["insufficient_payload"],"category_scores_codex":[0.001149129,0.002428808,0.001529368,0.008104403,0.002235393,0.006008529,0.002734373,0.001758066,0.832661],"category_scores_gemma":[0.00747136,0.00206591,0.001126625,0.009778256,0.0006455284,0.003430502,0.004386664,0.001536759,0.9226188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002482653,"about_ca_system_score_gemma":0.002354504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04025463,"about_ca_topic_score_gemma":0.05439622,"domain_scores_codex":[0.9991282,0.00007305107,0.00005565123,0.0001973579,0.0004064499,0.0001392817],"domain_scores_gemma":[0.9953396,0.0007090789,0.0001847159,0.001347638,0.00174591,0.0006730453],"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":[0.00002209516,0.000009182235,0.0001212767,0.0000908666,0.000003613888,0.000005905068,0.00003508361,0.00002103182,0.00008853291,0.0002772579,0.9883431,0.01098214],"study_design_scores_gemma":[0.00002059636,0.000004273963,0.0008848717,0.0000567835,0.000003518108,0.00002145853,0.00003084764,0.00006358189,0.0004484908,0.0003295172,0.9981207,0.0000153749],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003890445,0.0002403586,0.002692296,0.0004181965,0.0002389673,0.0001394519,0.6987636,0.09045026,0.2066679],"genre_scores_gemma":[0.001992668,0.0004387883,0.005177667,0.0004104758,0.0000977469,0.0002808154,0.5996894,0.08270378,0.3092087],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.167339,"threshold_uncertainty_score":0.2386888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007498927857950357,"score_gpt":0.1943529786851354,"score_spread":0.186854050827185,"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."}}