{"id":"W1999571649","doi":"10.1002/esp.1797","title":"Promise, performance and current limitations of a magnetic Bedload Movement Detector","year":2009,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; University of British Columbia","funders":"","keywords":"Bed load; Flume; Geology; Detector; Sediment transport; Particle (ecology); Sediment; SIGNAL (programming language); Fluvial; Computation; Magnetic field; Computer science; Mechanics; Geomorphology; Physics; Flow (mathematics)","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":[0.00009841609,0.0001185767,0.0001364974,0.00001766471,0.0001139374,0.0000151313,0.00006858386,0.00003887532,0.0001841651],"category_scores_gemma":[0.00001785566,0.00008469842,0.00001284022,0.0001571088,0.0001203902,0.0002544135,0.00002050715,0.00008075398,0.00001041206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003498304,"about_ca_system_score_gemma":0.00001745631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001292323,"about_ca_topic_score_gemma":0.00008985634,"domain_scores_codex":[0.9992861,0.000005553903,0.0001733886,0.0002024414,0.0001449457,0.0001875605],"domain_scores_gemma":[0.9997419,0.00002896056,0.00005796327,0.0000752598,0.00001624597,0.00007964675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001578572,0.0002915112,0.729625,0.0005576693,0.00001318925,0.00000206862,0.002757996,0.001212974,0.003393205,0.0000379632,0.00005737038,0.2618932],"study_design_scores_gemma":[0.0009903379,0.00130115,0.9689624,0.0000921458,0.00004169545,0.000005909515,0.00009201307,0.001562872,0.01618916,0.0008166083,0.009651998,0.0002937478],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951126,0.003253296,0.00007996327,0.0001728422,0.00002037966,0.0002009601,0.000005936743,0.00002264514,0.001131398],"genre_scores_gemma":[0.9949586,0.004281072,0.0004470871,0.0001039328,0.000006809462,0.000006918715,0.000005480109,0.000004025082,0.000186062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2615994,"threshold_uncertainty_score":0.3453901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01316239246853133,"score_gpt":0.2050860306169644,"score_spread":0.1919236381484331,"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."}}