{"id":"W2985255181","doi":"10.1002/ldr.3482","title":"Exploring soil amendment strategies with polyacrylamide to improve soil health and oat productivity in a dryland farming ecosystem: One‐time versus repeated annual application","year":2019,"lang":"en","type":"article","venue":"Land Degradation and Development","topic":"Polymer-Based Agricultural Enhancements","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China","keywords":"Environmental science; Soil quality; Agronomy; Soil health; Dryland farming; Soil retrogression and degradation; Productivity; Soil management; Agriculture; Soil organic matter; Agroforestry; Soil water; Soil science; Biology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001490325,0.0001741274,0.0002064338,0.00009499637,0.00006639451,0.00006532731,0.00003977544,0.00002740518,0.000002414869],"category_scores_gemma":[0.000004181176,0.0001357791,0.000006318071,0.0001623764,0.000005973439,0.0004040971,0.00002852531,0.00007474676,0.00001389797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002173724,"about_ca_system_score_gemma":0.00008754998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002482236,"about_ca_topic_score_gemma":0.002171917,"domain_scores_codex":[0.9989788,0.00002065418,0.0002519071,0.000318831,0.0001819565,0.000247858],"domain_scores_gemma":[0.9996597,0.00001990859,0.00006052185,0.0001075728,0.00002728949,0.000125054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001947663,0.0004127283,0.04153528,0.002462703,0.0004443408,0.000009673396,0.02722316,0.0237894,0.3308152,0.000301431,0.0001190562,0.5709394],"study_design_scores_gemma":[0.01813944,0.001963678,0.1640134,0.001761346,0.00005008533,0.00002994633,0.01609302,0.01411854,0.7740354,0.00004285414,0.006500731,0.00325153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975049,0.0001189546,0.001249043,0.0001268732,0.0001032697,0.0006355429,0.0000120035,0.0001067192,0.0001426172],"genre_scores_gemma":[0.9984387,0.00005668536,0.00102678,0.00002186637,0.00002442939,0.0002149036,0.0001038893,0.00001326284,0.00009946071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5676878,"threshold_uncertainty_score":0.5536911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02010564601913902,"score_gpt":0.2087505796594951,"score_spread":0.188644933640356,"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."}}