{"id":"W2126089837","doi":"10.4141/s99-003","title":"Assessing corn seedbed conditions for emergence","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Soil Science","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Seedbed; Sowing; Agronomy; Water content; Environmental science; Soil water; Field capacity; Tillage; Soil science; Biology; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002044309,0.0001820143,0.0001282793,0.0002114674,0.0001124098,0.0002087931,0.0001203142,0.0001389824,0.0009369717],"category_scores_gemma":[0.0003499815,0.0001247259,0.0001672193,0.0001280181,0.00006302266,0.0001845417,0.0001344428,0.0001887627,0.0001448849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002901199,"about_ca_system_score_gemma":0.0001377573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001964509,"about_ca_topic_score_gemma":0.007961784,"domain_scores_codex":[0.9998908,0.0000169474,0.000009495432,0.00004039958,0.00002855768,0.00001368344],"domain_scores_gemma":[0.9996554,0.00006465594,0.0001476578,0.00001520003,0.00004764094,0.00006950549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009198339,0.0001939598,0.5625088,0.00007571944,0.00005519687,0.00011872,0.0001154173,0.0004833896,0.425765,0.00003544499,0.00008376321,0.009644706],"study_design_scores_gemma":[0.000003324791,0.0002984032,0.9920833,0.000001979216,0.000007898597,0.00003291465,0.00002089218,0.0003556159,0.007099703,0.000005157332,0.00008829528,0.000002409398],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992195,0.0000661632,0.0003028628,0.000001837949,0.000001008916,0.00000928315,0.0001764116,0.000005848079,0.000216994],"genre_scores_gemma":[0.9986656,0.00003794665,0.0005706812,0.000005855594,7.598089e-7,0.00001626341,0.0004209519,0.000001973497,0.0002800653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001964509,"threshold_uncertainty_score":0.003906131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0175115582884329,"score_gpt":0.2626927325745321,"score_spread":0.2451811742860992,"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."}}