{"id":"W6980013208","doi":"","title":"ARCHIVEIT-2475-QUARTERLY-USMRBG-20110921215153-00002-crawling201.us.archive.org-6681.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":[0.0008037906,0.001529953,0.0008618367,0.005917472,0.001971954,0.005078208,0.001960179,0.001320317,0.8966715],"category_scores_gemma":[0.006616521,0.001329031,0.0007128192,0.01121985,0.000535078,0.002746776,0.002667509,0.001349626,0.9279448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002679004,"about_ca_system_score_gemma":0.002743216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09429801,"about_ca_topic_score_gemma":0.0875172,"domain_scores_codex":[0.9993777,0.00005910768,0.00004158388,0.0001034298,0.000299094,0.0001190774],"domain_scores_gemma":[0.9955661,0.0005746799,0.0002143565,0.0009334196,0.002078701,0.000632806],"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":[0.00001119105,0.000007969757,0.0001092138,0.00005514578,0.00000147059,0.000004673126,0.0000235681,0.00001596071,0.00003183145,0.0003274943,0.9887279,0.0106835],"study_design_scores_gemma":[0.00001216863,0.000003224322,0.0008451154,0.00005588746,0.000001743025,0.00001044407,0.00003729915,0.00002954176,0.0001728081,0.0001803416,0.998642,0.000009485726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003725631,0.0001792486,0.0008970686,0.0004669989,0.0002717929,0.0001261144,0.5251114,0.02218233,0.4503925],"genre_scores_gemma":[0.00198266,0.0004640192,0.00165426,0.0003979078,0.000119217,0.0002065545,0.2825317,0.02077194,0.6918718],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1033285,"threshold_uncertainty_score":0.1874983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00794461569819317,"score_gpt":0.1883321852218469,"score_spread":0.1803875695236537,"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."}}