{"id":"W2990715360","doi":"10.3390/ijgi8120523","title":"Multidimensional and Multiscale GIS","year":2019,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Geospatial analysis; Computer science; Process (computing); Data science; Data mining; Automation; Multidimensional data; Data quality; Multidimensional analysis; Geography; Engineering; Remote sensing; Metric (unit); Mathematics","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":[0.0007162921,0.0004957507,0.000498689,0.001842056,0.0004491867,0.003206806,0.0006974835,0.0007433932,0.006543188],"category_scores_gemma":[0.002170824,0.000293036,0.0006450462,0.002560448,0.001087375,0.002491622,0.002443408,0.0006689191,0.001312396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007938573,"about_ca_system_score_gemma":0.000596691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00191078,"about_ca_topic_score_gemma":0.002338663,"domain_scores_codex":[0.999227,0.0001532578,0.00004825903,0.0001799152,0.000337757,0.00005368231],"domain_scores_gemma":[0.9992569,0.0002041289,0.00005866534,0.000266121,0.000149065,0.00006517536],"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":[0.00002556579,0.00002845883,0.002982721,0.0003986406,0.00009623991,0.0003586593,0.0004267886,0.02657861,0.006430929,0.7294381,0.03055938,0.2026758],"study_design_scores_gemma":[0.00001033642,0.00003657479,0.007054572,0.0002015894,0.00004062894,0.0007433925,0.0004367998,0.07374626,0.002437803,0.4207457,0.4944913,0.00005502981],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02541919,0.01174788,0.8537425,0.006287194,0.00102606,0.000155832,0.00281476,0.002571291,0.0962352],"genre_scores_gemma":[0.2897015,0.01120732,0.6752344,0.001062799,0.001072438,0.0001861386,0.002279652,0.0004956332,0.01875999],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006543188,"threshold_uncertainty_score":0.02188915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002633569871327238,"score_gpt":0.2009884703038757,"score_spread":0.1983549004325484,"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."}}