{"id":"W1694250250","doi":"10.1080/13658816.2015.1047838","title":"A travel time-based variable grid approach for an activity-based cellular automata model","year":2015,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Cellular automaton; Variable (mathematics); Grid; Population; Euclidean distance; Euclidean geometry; Computer science; Geography; Mathematics; Algorithm; Artificial intelligence","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":[0.001449107,0.0001423843,0.0002444699,0.0002446618,0.00006784951,0.0002756716,0.0006033636,0.0001222218,0.00003156467],"category_scores_gemma":[0.00003658098,0.0001085516,0.0001396603,0.0001987184,0.00002303463,0.002283278,0.00003788603,0.0001295155,0.00004508808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001293635,"about_ca_system_score_gemma":0.0001037151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002827427,"about_ca_topic_score_gemma":0.000004656699,"domain_scores_codex":[0.9979413,0.00007383811,0.0006685049,0.0001100223,0.001020005,0.0001863403],"domain_scores_gemma":[0.9985632,0.00005441769,0.000634198,0.0001655825,0.0003237984,0.0002587625],"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":[0.0003837647,0.0002528702,0.002071685,0.00005160788,0.00006449993,0.000001122239,0.0001454602,0.9941753,0.0006089814,0.0001939169,0.001716901,0.000333935],"study_design_scores_gemma":[0.001921439,0.000227054,0.0003672046,0.00004088014,0.00002457004,0.00001960676,0.00008668657,0.9928929,0.0002807004,0.0001082139,0.003890746,0.0001399719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1950873,0.0000120836,0.7993382,0.0002269371,0.0007814873,0.0003795664,0.0001615175,0.0000388,0.003974143],"genre_scores_gemma":[0.9900941,0.000001006333,0.009167249,0.000292963,0.0002128883,0.0000309863,0.0001791734,0.000009211122,0.00001245516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7950068,"threshold_uncertainty_score":0.4426607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02379966821160748,"score_gpt":0.2409420781272661,"score_spread":0.2171424099156587,"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."}}