{"id":"W7099234205","doi":"","title":"MultivariateLagrangeInversion UniversityofWaterloo,Canada [summarybyDanieleGardy] BruceRichmond May25,1998","year":2008,"lang":"en","type":"article","venue":"","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vertex (graph theory); Product (mathematics); Ball (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":[],"consensus_categories":[],"category_scores_codex":[0.0007779818,0.001059087,0.0008581468,0.001506451,0.001193499,0.001764517,0.0007860505,0.0002902134,0.04431641],"category_scores_gemma":[0.003878253,0.0003358257,0.0005805848,0.004121347,0.001397461,0.0009640928,0.001096282,0.000960293,0.006191176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005282549,"about_ca_system_score_gemma":0.006506908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4404597,"about_ca_topic_score_gemma":0.6079447,"domain_scores_codex":[0.9995335,0.00005115517,0.00001797641,0.00009015695,0.0002496705,0.00005749907],"domain_scores_gemma":[0.9985645,0.0002303402,0.00006827109,0.0001370675,0.0009109681,0.00008871815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001076312,0.00005060405,0.00370764,0.0003368278,0.00006215293,0.0002387187,0.0002651447,0.02298724,0.001116481,0.1827876,0.3094511,0.478889],"study_design_scores_gemma":[0.00003891889,0.00004198999,0.01628278,0.0005038081,0.00006360278,0.0002842092,0.0002324169,0.09539177,0.002399248,0.1256855,0.7589266,0.0001491239],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0337539,0.09168967,0.4415213,0.01321936,0.007133335,0.0001929535,0.009247558,0.002817451,0.4004245],"genre_scores_gemma":[0.2215388,0.07291325,0.1052814,0.0007087887,0.003079934,0.0001595379,0.009580551,0.001395559,0.5853423],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4404597,"threshold_uncertainty_score":0.8757919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0107711924790518,"score_gpt":0.1757062487826411,"score_spread":0.1649350563035893,"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."}}