{"id":"W2772273493","doi":"10.1016/bs.agron.2017.11.003","title":"Distributed Temperature Sensing for Soil Physical Measurements and Its Similarity to Heat Pulse Method","year":2017,"lang":"en","type":"book-chapter","venue":"Advances in agronomy","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan; University of Alberta","funders":"","keywords":"Water content; Remote sensing; Calibration; Field (mathematics); Environmental science; Computer science; Soil science; Similarity (geometry); Process engineering; Data mining; Engineering; Geotechnical engineering; Geology; Artificial intelligence; Mathematics; Statistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002516654,0.0003997763,0.0005121518,0.00004338266,0.0002786027,0.00007475662,0.0001965635,0.0002399798,0.00001244686],"category_scores_gemma":[0.00008985848,0.0003525378,0.0001150763,0.00002378141,0.0001202422,0.0003264466,0.0002274277,0.0003603437,0.00002375705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002715809,"about_ca_system_score_gemma":0.00001778561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007524137,"about_ca_topic_score_gemma":0.002146755,"domain_scores_codex":[0.9983599,0.0000306249,0.0002317755,0.0007412277,0.0002769128,0.0003596293],"domain_scores_gemma":[0.9991916,0.000135081,0.0001145784,0.0003735447,0.00002724923,0.0001579873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002291351,0.00008316047,0.0009525768,0.0002061213,0.000122462,0.00006461734,0.0008805642,0.008532194,0.008347059,0.000509371,0.001772607,0.9783002],"study_design_scores_gemma":[0.002126145,0.0002668356,0.007498071,0.001513439,0.0003174693,0.00006072719,0.00007929303,0.003810954,0.01477799,0.03539431,0.9315788,0.002575966],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01646128,0.006568673,0.009343092,0.001784099,0.001478561,0.003844038,0.0001979317,0.0001388899,0.9601834],"genre_scores_gemma":[0.8454917,0.000903015,0.07590284,0.001658917,0.001884022,0.00002294525,0.0004613438,0.000305822,0.07336938],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9757242,"threshold_uncertainty_score":0.9998927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02414743455910763,"score_gpt":0.2968751457073333,"score_spread":0.2727277111482256,"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."}}