{"id":"W2883411541","doi":"10.1007/s12518-018-0233-3","title":"Generative HBIM modelling to embody complexity (LOD, LOG, LOA, LOI): surveying, preservation, site intervention—the Basilica di Collemaggio (L’Aquila)","year":2018,"lang":"en","type":"article","venue":"Applied Geomatics","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":171,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Photogrammetry; Process (computing); Architectural engineering; Engineering; Computer science; Construction engineering; Geography; 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":[0.0009807004,0.0005318685,0.0005386499,0.0005882381,0.0005247479,0.002020912,0.001550538,0.001159853,0.004190129],"category_scores_gemma":[0.003201051,0.00068052,0.001447642,0.0005660586,0.001708541,0.001527739,0.00252298,0.001231005,0.000501768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201146,"about_ca_system_score_gemma":0.0008782299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01496089,"about_ca_topic_score_gemma":0.01791201,"domain_scores_codex":[0.9995723,0.0001877865,0.00001943048,0.00008822455,0.00009152116,0.00004066172],"domain_scores_gemma":[0.9986738,0.0008905784,0.00005431227,0.0002082818,0.000103547,0.00006952172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005207235,0.00005243018,0.001710676,0.0001152877,0.00006694881,0.0001145842,0.0007313357,0.7345908,0.001968212,0.2195052,0.001803349,0.03928902],"study_design_scores_gemma":[0.000006738761,0.00001051941,0.0002343062,0.00002204001,0.00001204817,0.00003188952,0.00004185511,0.9481937,0.0006034075,0.04644134,0.004391108,0.00001097078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02075824,0.0001547794,0.9726634,0.000381288,0.00005160073,0.00003259011,0.0002073636,0.0006696151,0.005081229],"genre_scores_gemma":[0.6288885,0.0003511695,0.3607603,0.0001928589,0.00004821822,0.0001716341,0.0005811194,0.0007522762,0.008253714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01496089,"threshold_uncertainty_score":0.02974761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06339844609999955,"score_gpt":0.256394882583865,"score_spread":0.1929964364838654,"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."}}