{"id":"W2808461058","doi":"10.1007/s13593-018-0505-7","title":"New model-based insights for strategic nitrogen recommendations adapted to given soil and climate","year":2018,"lang":"en","type":"article","venue":"Agronomy for Sustainable Development","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Productivity; Soil water; Environmental science; Agriculture; Nitrogen; Limiting; Agronomy; Yield (engineering); Fertilizer; Crop yield; Reactive nitrogen; Agricultural productivity; Soil science; Ecology; Chemistry; Biology; Economics; Engineering","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":[0.001168742,0.0007854394,0.0009165123,0.0005110255,0.000417852,0.002149046,0.001352765,0.001823641,0.012106],"category_scores_gemma":[0.005608669,0.000566953,0.0006977278,0.0004918838,0.0006577254,0.003001191,0.0009002755,0.001733252,0.0004479593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002271933,"about_ca_system_score_gemma":0.002454103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01876242,"about_ca_topic_score_gemma":0.02280768,"domain_scores_codex":[0.9996889,0.0001388245,0.00001562838,0.00005493956,0.00005321523,0.00004854617],"domain_scores_gemma":[0.9984992,0.001013559,0.0001298731,0.00007090905,0.0001946249,0.00009190702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001859077,0.00004192499,0.0005448579,0.00003940423,0.0000189815,0.00006107559,0.00003998394,0.9165186,0.0003929299,0.07834283,0.001368806,0.002612029],"study_design_scores_gemma":[0.000008410379,0.000008997893,0.000148575,0.000009757679,0.000005962271,0.000009790949,0.00002863913,0.9367728,0.00006524372,0.06214802,0.0007851119,0.000008773043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1888057,0.0007665767,0.6719657,0.01145704,0.0004350893,0.0001464712,0.002724329,0.000391824,0.1233072],"genre_scores_gemma":[0.9520465,0.0004215498,0.03923139,0.0005098307,0.00008712048,0.0001143,0.0004233567,0.0001245834,0.007041402],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01876242,"threshold_uncertainty_score":0.04049861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02424007759596816,"score_gpt":0.2375550403759983,"score_spread":0.2133149627800302,"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."}}