{"id":"W2554481486","doi":"10.1007/978-3-319-17885-1_1603","title":"Integration of Spatial Constraint Databases","year":2017,"lang":"en","type":"book-chapter","venue":"Encyclopedia of GIS","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Database; Computer science; Constraint (computer-aided design); Spatiotemporal database; Information retrieval; Database design; Mathematics; Database tuning; View; Geometry","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":[0.0001964516,0.0002016511,0.0003483989,0.0001603937,0.00004574094,0.00004277803,0.001299281,0.00007377783,0.000231871],"category_scores_gemma":[0.0000760118,0.0001840868,0.0001066546,0.00001193331,0.0002111119,0.0005302629,0.0006214019,0.0001466811,0.00004429281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001262072,"about_ca_system_score_gemma":0.00008843913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003261594,"about_ca_topic_score_gemma":0.0001388063,"domain_scores_codex":[0.9987823,0.00001009413,0.0003861392,0.0003501611,0.0003503973,0.000120858],"domain_scores_gemma":[0.9978665,0.00005809336,0.0006455912,0.001289772,0.00009594243,0.0000441159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002651755,0.00001877345,0.00001490425,0.00005340017,0.00004048464,0.0000161186,0.00008279615,3.948072e-7,0.0000234239,0.4502275,0.006579055,0.5429405],"study_design_scores_gemma":[0.0002543869,0.0001152544,0.0004037977,0.0004337924,0.00006476771,0.000002845647,0.000006850361,0.0007519746,0.0003227705,0.01313815,0.984154,0.0003514063],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000007581182,0.0001064017,0.2185393,0.00008723341,0.0007200591,0.0001592556,0.0003154517,0.00002854965,0.7800362],"genre_scores_gemma":[0.004436563,0.004684393,0.1253827,0.00006148426,0.0008475085,0.00001192745,0.001119151,0.0000481122,0.8634082],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9775749,"threshold_uncertainty_score":0.7506844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0320672605272477,"score_gpt":0.2643638663434926,"score_spread":0.2322966058162449,"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."}}