{"id":"W4399506616","doi":"10.1186/s13007-024-01194-3","title":"A pin-based probe for electronic moisture meters to determine moisture content in a single wheat kernel","year":2024,"lang":"en","type":"article","venue":"Plant Methods","topic":"Agricultural Engineering and Mechanization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Government of Canada; Saskatchewan Wheat Development Commission; Alberta Wheat Commission; Ministry of Agriculture - Saskatchewan","keywords":"Water content; Agronomy; Straw; Moisture; Environmental science; Maturity (psychological); Crop; Grain quality; Agricultural engineering; Kernel (algebra); Mathematics; Biology; Engineering; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005285476,0.0005450285,0.0002848293,0.0004474862,0.0001386716,0.0002882311,0.0008462092,0.0005437593,0.003573206],"category_scores_gemma":[0.001026418,0.0002630198,0.0001905021,0.0002708027,0.0001696168,0.0004868071,0.0004968906,0.0003831148,0.0007426678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002225409,"about_ca_system_score_gemma":0.0001650061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002413476,"about_ca_topic_score_gemma":0.0005898887,"domain_scores_codex":[0.9994957,0.00008234361,0.00002652262,0.0001976065,0.0001671323,0.00003056632],"domain_scores_gemma":[0.9993914,0.0002426332,0.0001097374,0.00008584339,0.0001383849,0.00003195063],"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":[0.00014238,0.0000419102,0.002746006,0.0001191846,0.00001326523,0.00008365313,0.00005871728,0.0003188225,0.968212,0.0002526964,0.0005937644,0.0274175],"study_design_scores_gemma":[0.00003225297,0.0009473662,0.02409177,0.00002749671,0.00006943957,0.001257318,0.00008097153,0.02208473,0.9399217,0.0002149717,0.0112173,0.00005456293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.345662,0.0006455784,0.642599,0.0002486829,0.0003874975,0.0004824645,0.001086845,0.004673498,0.00421443],"genre_scores_gemma":[0.7167944,0.0002548231,0.2747349,0.0004390591,0.00004930967,0.0004216063,0.0004464721,0.0001719882,0.006687584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003573206,"threshold_uncertainty_score":0.01195359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03269538546400166,"score_gpt":0.2653631558803101,"score_spread":0.2326677704163085,"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."}}