{"id":"W578391238","doi":"10.1007/s10109-015-0222-6","title":"Testing block subdivision algorithms on block designs","year":2015,"lang":"en","type":"article","venue":"Journal of Geographical Systems","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Subdivision; Block (permutation group theory); Grid; Computer science; Algorithm; Scale (ratio); Minimum bounding box; Database; Data mining; Engineering; Geography; Mathematics; Artificial intelligence; Cartography; Civil engineering","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":[0.002543215,0.00009569267,0.0002213364,0.0002495375,0.0002781423,0.000131401,0.0001900576,0.000139123,0.000003556881],"category_scores_gemma":[0.0006769206,0.00007647921,0.00009893585,0.0007522505,0.00008545091,0.0001678721,0.000004817572,0.0002489195,0.000008925773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000478548,"about_ca_system_score_gemma":0.0001694698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005992338,"about_ca_topic_score_gemma":0.00002628246,"domain_scores_codex":[0.9978272,0.0003044558,0.0005186225,0.00011573,0.0009828964,0.0002511274],"domain_scores_gemma":[0.9980111,0.0003411145,0.0004310893,0.00007826077,0.0007623938,0.0003760649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003222561,0.0007195272,0.7099379,0.00006005554,0.0002033678,0.0003753112,0.01191183,0.2481205,0.0002603897,0.01213503,0.0108278,0.005126011],"study_design_scores_gemma":[0.01197986,0.01052721,0.6380759,0.005098392,0.000764302,0.0009368894,0.04466326,0.05826769,0.0001641785,0.004326466,0.2224513,0.002744485],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799284,0.0007762887,0.006474818,0.001111333,0.002955816,0.0003240127,0.000007811861,0.0001286376,0.008292867],"genre_scores_gemma":[0.9977905,0.0000188545,0.001383968,0.00003618512,0.0006590051,0.000001634698,0.000001609651,0.000009097026,0.00009921149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2116235,"threshold_uncertainty_score":0.3118731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08353725387069073,"score_gpt":0.3169565352879216,"score_spread":0.2334192814172309,"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."}}