{"id":"W2136942269","doi":"","title":"An airborne laser scanning approach to mapping and modelling surface moisture in an agricultural watershed in Nova Scotia","year":2009,"lang":"en","type":"dissertation","venue":"Masters Thesis","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Nova scotia; Watershed; Laser scanning; Nova (rocket); Environmental science; Geography; Remote sensing; Agriculture; Forestry; Hydrology (agriculture); Laser; Geology; Engineering; Archaeology; Computer science; Physics; Optics; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002632316,0.0003368545,0.0003990819,0.00006490092,0.00007553519,0.0001404874,0.0002767193,0.0003103999,0.00002460644],"category_scores_gemma":[0.000002167984,0.0001438348,0.0000632777,0.0004770461,0.00001402254,0.0002629494,0.000009855589,0.0002758644,0.000005582638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003882571,"about_ca_system_score_gemma":0.00000548106,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003628395,"about_ca_topic_score_gemma":0.02214665,"domain_scores_codex":[0.9982543,0.00009545069,0.0003506823,0.0006557468,0.0002574355,0.0003863924],"domain_scores_gemma":[0.9996133,0.00002442504,0.00007825786,0.00007691146,0.00003759582,0.0001694426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001540243,0.001861041,0.2919712,0.0003408012,0.00006303056,0.0000655035,0.05098887,0.1576744,0.3805712,0.00004301645,0.0002190344,0.1146617],"study_design_scores_gemma":[0.0002253564,0.0001532827,0.9785909,0.000248015,0.00001387589,0.000001120953,0.01592559,0.002639214,0.001676056,0.00001671357,0.00003907927,0.0004707983],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982212,0.00006855277,0.000006766723,0.0002180912,0.00007103475,0.0003952067,0.0000105379,0.00004874251,0.0009599034],"genre_scores_gemma":[0.9972649,0.00001207738,0.0007547315,0.0002268862,0.00006726696,0.000007476388,0.001389093,0.000003820709,0.0002737009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6866196,"threshold_uncertainty_score":0.9956966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03163352526804429,"score_gpt":0.2247719434182361,"score_spread":0.1931384181501918,"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."}}