{"id":"W4323076526","doi":"10.48550/arxiv.2303.01415","title":"Local data structures","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Data structure; Metric space; Context (archaeology); Theoretical computer science; Metric (unit); Set (abstract data type); Cluster analysis; Mathematics; Algorithm; Data mining; Discrete mathematics; Geography; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008881613,0.001074888,0.002541702,0.006242333,0.002540311,0.01304993,0.005303502,0.002534635,0.01353218],"category_scores_gemma":[0.05253058,0.001397248,0.00292136,0.009794757,0.004641667,0.02751353,0.009826445,0.004210519,0.00901788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002925964,"about_ca_system_score_gemma":0.003659626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002242888,"about_ca_topic_score_gemma":0.002007812,"domain_scores_codex":[0.9832343,0.002960033,0.003189419,0.004911477,0.005070967,0.0006337478],"domain_scores_gemma":[0.9582198,0.01212582,0.002511232,0.02080195,0.005203181,0.001137954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001611173,0.00007612709,0.004300301,0.0009697517,0.0001884735,0.0003943031,0.001382934,0.007033368,0.001994608,0.8246846,0.0316553,0.1271592],"study_design_scores_gemma":[0.00002891752,0.00008960011,0.0009187291,0.0002920298,0.0001022228,0.00080166,0.000493928,0.02069845,0.003800781,0.7526947,0.2199947,0.00008421286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006832263,0.002597987,0.9606346,0.002717668,0.0003491461,0.0004228606,0.01180156,0.004688099,0.009955797],"genre_scores_gemma":[0.1864064,0.004747025,0.7413974,0.002972813,0.001044699,0.002191407,0.03834854,0.002402424,0.02048919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01353218,"threshold_uncertainty_score":0.04697102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1986040978297434,"score_gpt":0.2164059414001464,"score_spread":0.01780184357040293,"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."}}