{"id":"W4403622663","doi":"10.48550/arxiv.2408.02812","title":"On Continuous Terminal Embeddings of Sets of Positive Reach","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Centre de Recherches Mathématiques; National Science Foundation","keywords":"Terminal (telecommunication); Mathematics; Computer science; Computer network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001502877,0.0001596539,0.0003165874,0.000394394,0.00003334723,0.00003481433,0.000713889,0.00013653,0.00004041478],"category_scores_gemma":[0.00002979913,0.0001693667,0.0002363547,0.0006030772,0.00006103804,0.00009314876,0.0009203572,0.0002519688,0.00002729388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007418163,"about_ca_system_score_gemma":0.0001334887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001186889,"about_ca_topic_score_gemma":0.000004622562,"domain_scores_codex":[0.9989355,0.00007204395,0.000213074,0.0005487491,0.0001151116,0.0001154924],"domain_scores_gemma":[0.9987596,0.0001166866,0.0003084904,0.0004616423,0.0002944492,0.0000591476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002581801,0.0001079151,0.0002464061,0.00007732959,0.0001997103,0.00009128359,0.0003500584,0.1773775,0.0000465732,0.820984,0.0002334218,0.000259952],"study_design_scores_gemma":[0.000205038,0.00009082463,0.0009530123,0.0002201808,0.0001716736,0.000003181721,0.0000405061,0.8787623,0.0005546354,0.1187833,0.00001556304,0.0001997759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3333412,0.00002952115,0.6485076,0.000273652,0.000355716,0.000212973,0.0001241953,0.0001064159,0.01704872],"genre_scores_gemma":[0.995649,0.00001769267,0.002360529,0.00004878903,0.00001323658,2.364588e-7,0.00002432139,0.00000704968,0.001879189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7022007,"threshold_uncertainty_score":0.6906571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03096945332520271,"score_gpt":0.1976152940981714,"score_spread":0.1666458407729687,"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."}}