{"id":"W2005032683","doi":"10.4141/cjss09015","title":"Identifying appropriate methodology to diagnose aeration limitations with large peat and bark particles in growing media","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Soil Science","topic":"Polymer-Based Agricultural Enhancements","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Institut National de la Recherche Agronomique","keywords":"Peat; Sawdust; Aeration; Bark (sound); Sphagnum; Thermal diffusivity; Bulk density; Environmental science; Chemistry; Horticulture; Pulp and paper industry; Soil science; Biology; Ecology; Soil water","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001835345,0.001162131,0.0007122006,0.00181339,0.0004467766,0.001137774,0.0007176877,0.001127152,0.001012961],"category_scores_gemma":[0.003718142,0.0004843218,0.0004551115,0.001012702,0.0006022649,0.0007689558,0.0007936304,0.00109049,0.0007928167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004419787,"about_ca_system_score_gemma":0.0006547468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002267891,"about_ca_topic_score_gemma":0.004073439,"domain_scores_codex":[0.998372,0.0003108189,0.000200728,0.0005366998,0.0004417176,0.0001380577],"domain_scores_gemma":[0.9972296,0.00105028,0.000721712,0.0002270371,0.0006225389,0.0001487285],"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":[0.00009214597,0.00005269059,0.004762677,0.0002819626,0.00001635651,0.00006269856,0.0001222075,0.0001814207,0.9820496,0.0000784209,0.00005078555,0.01224898],"study_design_scores_gemma":[0.00001609179,0.0006490857,0.04392602,0.0001047127,0.0001212505,0.0003542331,0.0004420653,0.005086169,0.9440523,0.0002907192,0.004903214,0.00005417519],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5445627,0.008093657,0.436875,0.0003336006,0.0003362301,0.001789841,0.001566898,0.00197125,0.004470754],"genre_scores_gemma":[0.4703467,0.004377916,0.5176309,0.0002069937,0.00004796191,0.003129905,0.00126692,0.0003835579,0.002609079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002267891,"threshold_uncertainty_score":0.009706378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04186141455293045,"score_gpt":0.254896806016878,"score_spread":0.2130353914639475,"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."}}