{"id":"W2199344813","doi":"10.1139/cgj-2015-0253","title":"Improved image-based deformation measurement for geotechnical applications","year":2015,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":442,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Lloyd's Register","keywords":"Particle image velocimetry; Geotechnical engineering; Centrifuge; Deformation (meteorology); Displacement (psychology); Geology; Engineering; Mechanics; Turbulence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.002493783,0.0002115422,0.0002320377,0.0003589804,0.0002975333,0.0004939027,0.00144564,0.0002352011,0.00001555676],"category_scores_gemma":[0.0006494959,0.0001874859,0.0001840399,0.0003731959,0.0001028938,0.0006876452,0.00006919759,0.0005597351,0.00003737804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001404287,"about_ca_system_score_gemma":0.00216833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005902563,"about_ca_topic_score_gemma":0.0006716406,"domain_scores_codex":[0.9977221,0.00006642169,0.0005705428,0.0003240162,0.0006396058,0.0006772473],"domain_scores_gemma":[0.9962206,0.00004493208,0.0001653232,0.0005707422,0.001511273,0.001487112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002957865,0.001030725,0.000104719,0.0001984714,0.0002253755,0.00007068231,0.0002515571,0.003599535,0.05958449,0.2545446,0.1804683,0.4996257],"study_design_scores_gemma":[0.002084755,0.001720036,0.0001564177,0.0001668965,0.00006241428,0.0002180563,0.00005004284,0.6531907,0.01873028,0.05821399,0.2644239,0.0009825166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00008067981,0.00009557661,0.988453,0.009074254,0.0001859804,0.0008624227,0.000008518491,0.0003239751,0.0009155873],"genre_scores_gemma":[0.8594746,0.000006391257,0.1383132,0.001497754,0.000243527,0.0004180039,0.000006989797,0.00002131759,0.00001824677],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8593939,"threshold_uncertainty_score":0.7645453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0640117923835182,"score_gpt":0.2716737198151028,"score_spread":0.2076619274315846,"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."}}