{"id":"W4385291775","doi":"10.48550/arxiv.2307.13046","title":"Skydiving to Bootstrap Islands","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Colleges and Universities; European Commission; Institut Périmètre de physique théorique; Innovation, Science and Economic Development Canada; Resnick Sustainability Institute for Science, Energy and Sustainability, California Institute of Technology; Government of Canada; California Institute of Technology; U.S. Department of Energy","keywords":"Space (punctuation); Computation; Point (geometry); Parameter space; Conformal map; Test (biology); Process (computing); Mathematical optimization; Medicine; Applied mathematics; Mathematics; Algorithm; Computer science; Statistics; Mathematical analysis; Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003481862,0.0003212106,0.000397785,0.0005578267,0.0001604043,0.00007683664,0.0009018575,0.0003069199,0.0002932861],"category_scores_gemma":[0.0006131534,0.000388854,0.0001860648,0.0009009846,0.00007010249,0.0001278039,0.001947316,0.000762055,0.0006698839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003138677,"about_ca_system_score_gemma":0.0001611852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003496252,"about_ca_topic_score_gemma":0.00006838272,"domain_scores_codex":[0.9979912,0.0001084904,0.0002501055,0.0009494071,0.0001876224,0.0005131417],"domain_scores_gemma":[0.9978015,0.0004328822,0.0001585762,0.001044846,0.0002717723,0.000290454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005397618,0.0001181425,0.001274585,0.0003220384,0.0001870533,0.0005928261,0.0006042935,0.9317687,0.00001785176,0.05748644,0.007186304,0.0003877734],"study_design_scores_gemma":[0.0007897543,0.00007905954,0.0005949045,0.0003747192,0.0001192175,0.000004525487,0.0006846443,0.5343235,0.0001332681,0.4600881,0.001763518,0.001044769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04213809,0.000009133076,0.9498109,0.0002029334,0.0004747794,0.0007311645,0.00009091224,0.0007850353,0.005757072],"genre_scores_gemma":[0.8835642,0.0001790434,0.03466904,0.00008237033,0.0002277334,0.00000668055,0.00004559227,0.0001697101,0.08105557],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9151418,"threshold_uncertainty_score":0.9998564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3285378716142433,"score_gpt":0.3056362727331225,"score_spread":0.02290159888112075,"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."}}