{"id":"W2132366220","doi":"10.1002/esp.2045","title":"Development of an automated method for continuous detection and quantification of cliff erosion events","year":2010,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Coastal and Marine Dynamics","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Northern Studies; Université du Québec à Rimouski","funders":"","keywords":"Cliff; Erosion; Snow; Environmental science; Coastal erosion; Precipitation; Geology; Hydrology (agriculture); Thermocouple; Snowmelt; Remote sensing; Meteorology; Geomorphology; Geotechnical engineering; Materials science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003038895,0.00007222709,0.000135156,0.00002857811,0.00008722204,0.00001459784,0.00004161963,0.00004997677,0.00001529392],"category_scores_gemma":[0.00003895835,0.00004942669,0.00001093672,0.00008933658,0.00002466747,0.0001640117,0.000009527388,0.00004613634,4.539221e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":3.060514e-7,"about_ca_system_score_gemma":0.00003866815,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005368289,"about_ca_topic_score_gemma":0.02203543,"domain_scores_codex":[0.9994822,0.000008009119,0.0001928088,0.0001355645,0.00008353659,0.00009784564],"domain_scores_gemma":[0.9996153,0.00005416615,0.0001230567,0.00005675793,0.0000995704,0.00005113702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003022852,0.00005847475,0.2498354,0.0008088085,0.0000173564,1.540158e-7,0.0008657845,0.0003806394,0.07035496,0.0000193605,9.762986e-7,0.6773558],"study_design_scores_gemma":[0.0005029915,0.0002583271,0.7327209,0.00002744943,0.0000141406,0.00000783034,0.0002474773,0.2052462,0.05978783,0.000256415,0.0008020532,0.0001283438],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880606,0.00004928821,0.01150923,0.000008741945,0.00007216432,0.0001875937,0.00004726456,0.00003168709,0.00003341273],"genre_scores_gemma":[0.9515409,0.00002659583,0.04827255,0.000003314784,0.000006769739,0.000001069668,0.0000976038,0.000002238421,0.0000489533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6772274,"threshold_uncertainty_score":0.9958099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087831955610044,"score_gpt":0.255135099615857,"score_spread":0.2442567800597565,"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."}}