{"id":"W3119950802","doi":"10.1007/s11629-020-6552-y","title":"Field testing innovative differential geospatial and photogrammetric monitoring technologies in mountainous terrain near Ashcroft, British Columbia, Canada","year":2021,"lang":"en","type":"article","venue":"Journal of Mountain Science","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Geological Survey of Canada","funders":"University of Alberta; Queen's University; British Geological Survey; University College Dublin; Government of Canada","keywords":"Landslide; Interferometric synthetic aperture radar; Terrain; Geospatial analysis; Natural hazard; Geohazard; Photogrammetry; GNSS applications; Geology; Remote sensing; Geodetic datum; Synthetic aperture radar; Geography; Cartography; Global Positioning System; Meteorology; Geodesy; Telecommunications; Seismology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006489121,0.00009985521,0.0002300028,0.00008738009,0.000378094,0.0006034654,0.000408025,0.0000882012,0.00008739893],"category_scores_gemma":[0.001641696,0.0001103521,0.0000241804,0.002986013,0.0004253551,0.0003782265,0.0004168171,0.0005150101,5.960429e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006379944,"about_ca_system_score_gemma":0.0006382753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7175201,"about_ca_topic_score_gemma":0.6711265,"domain_scores_codex":[0.9980559,0.0000368441,0.0004332607,0.0002803619,0.0007693635,0.0004242527],"domain_scores_gemma":[0.9991921,0.0001778285,0.0002597295,0.0001315534,0.0001460694,0.00009272952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009549382,0.00003986723,0.8865774,0.000005493144,0.000006039451,0.0006348342,0.0001726682,0.000164154,0.01090374,8.96263e-7,0.0001443739,0.101341],"study_design_scores_gemma":[0.0007149734,0.0003056103,0.9855264,0.0001706507,0.00001078755,0.001090484,0.003165273,0.001919471,0.006037598,0.000248796,0.0005624705,0.0002475173],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987071,0.0001969972,0.0001622026,0.0001804265,0.0003734757,0.0000755615,0.000002830123,0.00001226514,0.000289187],"genre_scores_gemma":[0.997305,0.00006700924,0.002443048,0.0000606987,0.00004002758,0.000002073779,2.904351e-7,0.000006693542,0.00007511926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1010935,"threshold_uncertainty_score":0.5819231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007526315380012707,"score_gpt":0.2175168522644417,"score_spread":0.209990536884429,"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."}}