{"id":"W2083392507","doi":"10.1068/b31159","title":"A Precategorical Spatial-Data Metamodel","year":2006,"lang":"en","type":"article","venue":"Environment and Planning B Planning and Design","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Wilfrid Laurier University","funders":"","keywords":"Formalism (music); Metamodeling; Computer science; Spatial analysis; Graph; Graph theory; Land use; Data mining; Theoretical computer science; Geography; Mathematics; Engineering; Software engineering; Remote sensing","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":[0.004410151,0.0005344317,0.000605655,0.002133297,0.001022378,0.00541226,0.002491545,0.001610008,0.00402622],"category_scores_gemma":[0.0057981,0.0005305209,0.001588112,0.00240036,0.003220462,0.007247509,0.003076728,0.00256722,0.00125097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001754595,"about_ca_system_score_gemma":0.003295126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002832629,"about_ca_topic_score_gemma":0.003094406,"domain_scores_codex":[0.9971317,0.0009160465,0.0004192683,0.0006242103,0.0007430181,0.0001657335],"domain_scores_gemma":[0.9964856,0.001125254,0.000198749,0.001383902,0.0005914697,0.0002150238],"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":[0.00001212143,0.0000152622,0.0003079369,0.00004778134,0.00000981616,0.00005269309,0.0001356325,0.007733801,0.0004872835,0.9808606,0.0009609073,0.009376016],"study_design_scores_gemma":[0.00002153338,0.00003996854,0.0001680357,0.0001188272,0.00004030261,0.0002904941,0.0001984377,0.1131824,0.002807808,0.773149,0.1099555,0.0000276298],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002905274,0.00009474735,0.9893898,0.001054527,0.00006390343,0.00006161472,0.0004847415,0.0003860392,0.005559291],"genre_scores_gemma":[0.1513721,0.00049272,0.8370275,0.0006350306,0.0001012671,0.0004222075,0.001826672,0.0001941268,0.007928309],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00541226,"threshold_uncertainty_score":0.02332336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06228428375335177,"score_gpt":0.2423044475476431,"score_spread":0.1800201637942914,"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."}}