{"id":"W4230892244","doi":"10.32920/ryerson.14655639.v1","title":"Scatter Search on a Disk","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Robot; Upper and lower bounds; Carry (investment); Unit disk; Object (grammar); Computer science; Combinatorics; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002967746,0.0001428543,0.0001548942,0.0001320498,0.00006507723,0.0009100904,0.001161086,0.0001049281,0.0006690053],"category_scores_gemma":[0.00001854431,0.0001197381,0.00009698616,0.0002032558,0.00002641964,0.0001287349,0.002703956,0.0005848343,0.0003486994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004431719,"about_ca_system_score_gemma":0.0002425523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005231018,"about_ca_topic_score_gemma":0.00000838496,"domain_scores_codex":[0.998307,0.0001395335,0.00015976,0.0006404433,0.0004911669,0.0002620658],"domain_scores_gemma":[0.9985355,0.0000525446,0.00002708619,0.001098498,0.0001584554,0.0001279718],"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":[0.00001450312,0.001191323,0.001369004,0.0004493865,0.0002448792,0.0002799427,0.007242062,0.3141484,0.0002641307,0.2963008,0.195115,0.1833805],"study_design_scores_gemma":[0.0002945166,0.00007696555,0.0008688624,0.0001963188,0.000002757694,0.000006439689,0.00005657462,0.982792,0.001597729,0.001973488,0.01160847,0.0005259135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009708675,0.00003060165,0.9140017,0.02481283,0.0004436744,0.000238754,0.000001768926,0.0002157875,0.05928402],"genre_scores_gemma":[0.3471379,0.0003696572,0.5650852,0.04137327,0.0001915331,0.0001531561,0.00011623,0.00005203152,0.04552099],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6686435,"threshold_uncertainty_score":0.8776023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0489022449323859,"score_gpt":0.3063104859897336,"score_spread":0.2574082410573478,"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."}}