{"id":"W3013782026","doi":"","title":"基于Bayes-MeTiS网格划分的3D几何重构 (3D Geometric Reconstruction Based on Bayes-MeTiS Mesh Partition).","year":2018,"lang":"en","type":"article","venue":"计算机科学","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metis; Bayes' theorem; Partition (number theory); Computer science; Artificial intelligence; Mathematics; Combinatorics; Bayesian probability; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002439994,0.001545779,0.001485584,0.003326912,0.002231478,0.001745857,0.002658453,0.0009132769,0.001802617],"category_scores_gemma":[0.0008909736,0.001548384,0.0007481741,0.00726789,0.001295235,0.003150588,0.0005758652,0.001503172,0.003514526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008160222,"about_ca_system_score_gemma":0.001186764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000318738,"about_ca_topic_score_gemma":0.0001950584,"domain_scores_codex":[0.9890189,0.0008413051,0.002099597,0.003340358,0.002234189,0.002465703],"domain_scores_gemma":[0.9923244,0.000751591,0.001330531,0.003096809,0.001517166,0.0009794892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003279156,0.0009528896,0.005468804,0.0002642649,0.0002597106,0.0001553437,0.0007056458,0.0004489925,0.002665094,0.005114685,0.01981805,0.9638186],"study_design_scores_gemma":[0.01540078,0.008211208,0.03407336,0.002755484,0.0008634068,0.004133779,0.0006726948,0.5752719,0.1067597,0.01696718,0.2244165,0.010474],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08244347,0.001377156,0.8197894,0.004321668,0.02721411,0.002952524,0.0002390257,0.004839204,0.05682346],"genre_scores_gemma":[0.8150814,0.0002906766,0.1705327,0.00333437,0.004501479,0.0005300766,0.0001585586,0.0003052639,0.005265469],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9533446,"threshold_uncertainty_score":0.9997291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01067225617562672,"score_gpt":0.2308482388898727,"score_spread":0.220175982714246,"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."}}