{"id":"W7040380882","doi":"","title":"EXD-16-04-03","year":2016,"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":"Offensive; Set (abstract data type); Feature (linguistics); Offset (computer science); Noise (video)","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":[0.000636904,0.0005956389,0.0004335476,0.0007101772,0.001770221,0.003555929,0.0008040292,0.001566072,0.8776703],"category_scores_gemma":[0.001938417,0.0002898606,0.0003170158,0.000512285,0.0004353765,0.001361432,0.001963691,0.00150397,0.7987366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342113,"about_ca_system_score_gemma":0.0008521155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007490777,"about_ca_topic_score_gemma":0.01986963,"domain_scores_codex":[0.9997054,0.00003288821,0.000009027592,0.00005031437,0.0001305686,0.00007175859],"domain_scores_gemma":[0.9991304,0.00007125394,0.00001999911,0.0001173939,0.0003797614,0.000281255],"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":[0.00009362179,0.0000331748,0.0001815912,0.00005996133,0.000002543924,0.00004447779,0.00005999782,0.00003136574,0.0005762582,0.002991284,0.9715586,0.02436706],"study_design_scores_gemma":[0.00001374675,0.00001521271,0.0003354301,0.00003015661,0.000001199137,0.00002122952,0.0000521894,0.00003039887,0.0001854394,0.000295602,0.9990152,0.000004123817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004226677,0.00009912885,0.0005067187,0.0007035173,0.001273622,0.00009189855,0.006871338,0.001975119,0.9880561],"genre_scores_gemma":[0.00180787,0.0000541926,0.0001997935,0.000203511,0.0001069367,0.00002609759,0.002522095,0.0008121594,0.9942673],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1223297,"threshold_uncertainty_score":0.1744884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006569427091373487,"score_gpt":0.1974599586482889,"score_spread":0.1908905315569155,"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."}}