{"id":"W6992729484","doi":"","title":"2015 05 09 Michel Marc Entrevue IO","year":2015,"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":"MAGIC (telescope); Instant; Reel; EPIC","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":[0.0005392678,0.0009271023,0.0004954786,0.001467971,0.001894076,0.004959691,0.0006808544,0.00181518,0.6997047],"category_scores_gemma":[0.001760195,0.0002801239,0.0003664765,0.0006832103,0.0004931175,0.001723401,0.002513054,0.001655529,0.5208598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00190185,"about_ca_system_score_gemma":0.001392308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009362566,"about_ca_topic_score_gemma":0.02287861,"domain_scores_codex":[0.9994916,0.00004927109,0.00001468273,0.00008709342,0.0002402306,0.0001171823],"domain_scores_gemma":[0.9994727,0.00005223262,0.00002574983,0.00005467535,0.0001606655,0.0002340854],"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":[0.0000392785,0.00001750957,0.000135924,0.00007206896,0.000002431242,0.0001392775,0.0001015996,0.00003488439,0.0003615675,0.006170914,0.9415787,0.05134584],"study_design_scores_gemma":[0.000001738042,0.00000347604,0.0001530173,0.00002450805,4.569223e-7,0.00004196279,0.00002720774,0.00001240615,0.00006173286,0.0001599661,0.9995114,0.000002159541],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005416847,0.003148729,0.0003074762,0.002843712,0.006400459,0.00004644897,0.001117112,0.0008421895,0.9847524],"genre_scores_gemma":[0.002031158,0.0004333594,0.0001010813,0.0002693404,0.0003557744,0.00001167132,0.0002341981,0.0002096612,0.9963537],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3002953,"threshold_uncertainty_score":0.4283348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008188677475629918,"score_gpt":0.2029073769391866,"score_spread":0.1947186994635567,"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."}}