{"id":"W15302468","doi":"","title":"Synthetic and Real Spatiotemporal Datasets.","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Benchmarking; Computer science; Context (archaeology); Data science; Data mining; Synthetic data; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004844191,0.0005554248,0.0004047416,0.002557843,0.0006907422,0.001095301,0.001578403,0.001105092,0.002830202],"category_scores_gemma":[0.02301883,0.0002259067,0.0008070185,0.005728109,0.0007417215,0.001692868,0.001323033,0.0008943549,0.001072943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009325747,"about_ca_system_score_gemma":0.001280663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004292054,"about_ca_topic_score_gemma":0.00797211,"domain_scores_codex":[0.9958859,0.001834106,0.0005568817,0.0005834512,0.0009656621,0.0001739884],"domain_scores_gemma":[0.9833717,0.007562736,0.001180279,0.004611071,0.002767829,0.0005064162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002009897,0.002378862,0.08587642,0.003912221,0.0009776991,0.002686611,0.001252381,0.3188797,0.01074009,0.05730708,0.3536394,0.1603396],"study_design_scores_gemma":[0.0005955087,0.001307943,0.07362221,0.0005708559,0.0003088024,0.004403749,0.004180897,0.5002371,0.01892366,0.07171774,0.3238283,0.0003032655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3999138,0.002540469,0.16828,0.005803822,0.002096414,0.002218908,0.3953832,0.00447557,0.01928793],"genre_scores_gemma":[0.4631725,0.001136866,0.1256968,0.0006435932,0.0002998103,0.001790935,0.4045504,0.0002370535,0.002472006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004844191,"threshold_uncertainty_score":0.02561885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410719613160535,"score_gpt":0.2333191480502406,"score_spread":0.2192119519186353,"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."}}