{"id":"W4402262518","doi":"10.62973/09-037r1","title":"OWS-6 UTDS-CityGML Implementation Profile","year":2009,"lang":"en","type":"report","venue":"","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense; Natural Resources Canada; U.S. Geological Survey","keywords":"CityGML; Computer science; Data mining; Visualization","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001894033,0.0002694779,0.000265334,0.0001313544,0.00005553324,0.00005243271,0.000199908,0.0002517799,0.001601765],"category_scores_gemma":[0.00001458621,0.0002793952,0.0000971734,0.0001572723,0.00001089809,0.00007508398,0.00002856444,0.0002923177,0.0003974967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003825066,"about_ca_system_score_gemma":0.0002628557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006267289,"about_ca_topic_score_gemma":0.000462548,"domain_scores_codex":[0.9984708,0.000006988865,0.0004668637,0.0002744148,0.0004994386,0.0002814932],"domain_scores_gemma":[0.9990982,0.0000172225,0.00007701496,0.0004597233,0.0002745599,0.00007322436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[7.336808e-7,0.00003098873,0.00008798867,0.0002624679,0.0001044549,0.000002766623,0.00008080313,0.01338878,0.0003944859,0.0005435123,0.7432126,0.2418904],"study_design_scores_gemma":[0.000231951,0.00004608351,0.001428513,0.0000734858,0.0001364984,0.00002330879,0.00004486684,0.03803109,0.003166639,0.001250879,0.9546618,0.000904913],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0008805663,0.0004754509,0.188077,0.0001284372,0.001029788,0.001344916,0.0002379808,0.002185575,0.8056403],"genre_scores_gemma":[0.5346873,0.009568591,0.306154,0.0005877907,0.009296129,0.005295866,0.02290083,0.00129448,0.110215],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6954253,"threshold_uncertainty_score":0.9999658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02921071072396622,"score_gpt":0.3197597496487503,"score_spread":0.2905490389247841,"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."}}