{"id":"W2897480887","doi":"10.1680/jmaen.2018.17","title":"Innovative use of GIS and drone photogrammetry for cliff stability modelling","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Institution of Civil Engineers - Maritime Engineering","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Esri (Canada); W.F. Baird & Associates Coastal Engineers (Canada); Golder Associates (Canada)","funders":"","keywords":"Photogrammetry; Cliff; Drone; Remote sensing; Digital elevation model; Terrain; Geology; Geographic information system; Point cloud; Cartography; Geography; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004191047,0.0001374877,0.0002475826,0.00009726076,0.00006594669,0.00001954448,0.0001499161,0.0000774666,0.00002724141],"category_scores_gemma":[0.000365237,0.0001088773,0.00006345222,0.000517419,0.0002278274,0.0003826276,0.00002224662,0.0001125745,2.54426e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008590321,"about_ca_system_score_gemma":0.00002207613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005031417,"about_ca_topic_score_gemma":0.00008316441,"domain_scores_codex":[0.9991173,0.000003689392,0.0003430055,0.0001616427,0.0001868759,0.0001875303],"domain_scores_gemma":[0.9991721,0.0001134149,0.0001400782,0.00007432956,0.0004525739,0.0000474953],"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":[0.0006802948,0.0002175079,0.374586,0.006590117,0.0005282358,5.519383e-7,0.005256875,0.4920717,0.0916978,0.01293468,0.0004332683,0.01500303],"study_design_scores_gemma":[0.000416145,0.0002261329,0.02870431,0.0003608376,0.00003634809,0.00000496541,0.0002427108,0.9027684,0.06612334,0.0001651221,0.0007134478,0.0002381815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758672,0.0001418908,0.02281156,0.00002036193,0.0002023183,0.0002725715,0.0001186036,0.00003737886,0.0005280991],"genre_scores_gemma":[0.990557,0.00001821749,0.009340261,0.00000572485,0.00004275056,0.000002642716,0.000008917497,0.000005246189,0.00001923519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4106968,"threshold_uncertainty_score":0.4439889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02890235832647606,"score_gpt":0.1969477255209697,"score_spread":0.1680453671944937,"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."}}