{"id":"W2152273606","doi":"10.1016/s0169-555x(02)00355-0","title":"Landslide inventory in a rugged forested watershed: a comparison between air-photo and field survey data","year":2003,"lang":"en","type":"article","venue":"Geomorphology","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":248,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Landslide; Geology; Debris; Hydrology (agriculture); Watershed; Aerial photos; Structural basin; Terrain; Colluvium; Drainage basin; Sediment; Aerial photography; Physical geography; Geomorphology; Remote sensing; Cartography; Geography; Geotechnical engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009188112,0.0001353606,0.000289747,0.00004797404,0.00006646505,0.00001293974,0.0003001866,0.0002100495,0.001553428],"category_scores_gemma":[0.0001589453,0.0001068493,0.00001755472,0.0001715525,0.0001317655,0.0000994906,0.0003407014,0.0002714407,0.0001487233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004009212,"about_ca_system_score_gemma":0.0000127556,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007953024,"about_ca_topic_score_gemma":0.01522586,"domain_scores_codex":[0.9985062,0.0003005604,0.0002785976,0.0004194655,0.0001228959,0.0003722527],"domain_scores_gemma":[0.9991871,0.0001783999,0.00006644434,0.0004528218,0.000004304017,0.0001109185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000384913,0.00003728771,0.9840801,0.000004087175,0.00001321583,0.00004729443,0.0002228702,0.00005514305,0.0001707538,0.000006333362,0.01467699,0.0006474525],"study_design_scores_gemma":[0.001434657,0.0001612722,0.9483,0.00001035559,0.00002151697,0.00005386443,0.00008107166,0.0004643904,0.0005993135,0.0002268982,0.04841887,0.0002277828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968621,0.00009820759,0.0001409345,0.0001776992,0.0001212037,0.0001736923,0.00006728093,0.00001948095,0.002339389],"genre_scores_gemma":[0.9985181,0.00003682603,0.0002392305,0.0004064291,0.00001240259,0.000006794151,0.0004836609,0.00001143418,0.0002851116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03578007,"threshold_uncertainty_score":0.9993593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04122562360235429,"score_gpt":0.2756824177846062,"score_spread":0.2344567941822519,"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."}}