{"id":"W2902857675","doi":"10.1145/3272127.3275042","title":"OptCuts","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada; Skolkovo Institute of Science and Technology; National Science Foundation","keywords":"Distortion (music); Embedding; Upper and lower bounds; Computer science; Scalability; Algorithm; Bijection; Benchmark (surveying); Distortion function; Range (aeronautics); Scratch; Discontinuity (linguistics); Surface (topology); Topology (electrical circuits); Mathematics; Geometry; Artificial intelligence; Discrete mathematics; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006828184,0.001888946,0.001059534,0.001160317,0.0008528015,0.002285921,0.003157038,0.001910204,0.04561018],"category_scores_gemma":[0.003288502,0.001095779,0.001622468,0.0009674777,0.0009144651,0.002108853,0.003419399,0.002201949,0.01107635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006625478,"about_ca_system_score_gemma":0.001039881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00186557,"about_ca_topic_score_gemma":0.004582707,"domain_scores_codex":[0.9991611,0.00007799661,0.00005690691,0.0001504451,0.0004729256,0.00008055187],"domain_scores_gemma":[0.9992392,0.0002418169,0.00005691179,0.0002533112,0.0001624975,0.00004623231],"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":[0.0003437045,0.0001468141,0.001408358,0.001139208,0.000164333,0.0003313043,0.0003430117,0.0980763,0.02250723,0.07588241,0.1155905,0.6840668],"study_design_scores_gemma":[0.0002034471,0.0002015749,0.0006591394,0.0002238991,0.00005173039,0.00087176,0.0002052305,0.5929676,0.03194163,0.1008266,0.2717468,0.0001005452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006253127,0.0005733991,0.9455923,0.0002128368,0.0003098172,0.0002230904,0.001259269,0.02708784,0.01848836],"genre_scores_gemma":[0.08663612,0.0006982245,0.8628475,0.0004930539,0.00009624712,0.0006461094,0.006478497,0.02006351,0.02204067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04561018,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01316880082188389,"score_gpt":0.2554402378666854,"score_spread":0.2422714370448015,"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."}}