{"id":"W2907466780","doi":"10.1109/icsens.2018.8589802","title":"Low-Cost 3D-Printed Wireless Soil Moisture Sensor","year":2018,"lang":"en","type":"article","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Water content; Moisture; Environmental science; Antenna (radio); Remote sensing; Fabrication; Wireless; Wireless sensor network; Soil moisture sensor; Altitude (triangle); Computer science; Electronic engineering; Engineering; Materials science; Geology; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008121741,0.0002374808,0.0003115079,0.0002772501,0.0000949473,0.0003223999,0.0006229194,0.0005765106,0.001409522],"category_scores_gemma":[0.0002587857,0.0002000325,0.0002524656,0.000253393,0.0001258079,0.0004355911,0.0002527842,0.0002889118,0.000685842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001569442,"about_ca_system_score_gemma":0.0001145876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002162267,"about_ca_topic_score_gemma":0.00041115,"domain_scores_codex":[0.9997599,0.00001622927,0.000009211302,0.00004311616,0.0001593643,0.00001231102],"domain_scores_gemma":[0.9998418,0.00003715888,0.00004247446,0.00002458496,0.00004281323,0.00001118842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004885855,0.00002596876,0.0004311446,0.000154156,0.00001245544,0.0002057248,0.00001744159,0.00284467,0.9591292,0.0003047966,0.0007648703,0.03606078],"study_design_scores_gemma":[0.00001632645,0.0003562532,0.004793326,0.0000129979,0.00003608569,0.001273428,0.00002358998,0.03933278,0.9365687,0.0002642263,0.01727661,0.00004567688],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4152025,0.00212745,0.563902,0.0004320669,0.0005193141,0.0001296374,0.001318218,0.004417181,0.01195159],"genre_scores_gemma":[0.7965958,0.0007343897,0.1860666,0.0002266322,0.00006590746,0.00009647544,0.000568221,0.00007636013,0.01556975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001409522,"threshold_uncertainty_score":0.004715323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008018933679582844,"score_gpt":0.2219584246686511,"score_spread":0.2139394909890683,"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."}}