{"id":"W1970742700","doi":"10.1071/sr13238","title":"Scaling of pores in 3D images of Latosols (Oxisols) with contrasting mineralogy under a conservation management system","year":2014,"lang":"en","type":"article","venue":"Soil Research","topic":"Soil Management and Crop Yield","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Latosol; Oxisol; Saprolite; Soil water; Soil science; Mineralogy; Granulometry; Geology; Geostatistics; Image resolution; Materials science; Spatial variability; Environmental science; Geomorphology; Mathematics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002471311,0.0002489907,0.000178193,0.001951966,0.0001668735,0.0006900172,0.0001589671,0.0002795991,0.0006542797],"category_scores_gemma":[0.0005287228,0.0002268817,0.0002456124,0.0007059671,0.0003523038,0.0003694012,0.0004653304,0.0002340834,0.0001119777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002150667,"about_ca_system_score_gemma":0.000216801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002429237,"about_ca_topic_score_gemma":0.005116445,"domain_scores_codex":[0.9998522,0.00001517909,0.00001011045,0.00003724015,0.00005559079,0.00002972619],"domain_scores_gemma":[0.9996138,0.0001249588,0.0001002331,0.00003225136,0.00009067797,0.00003804976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006133182,0.00008631551,0.1322016,0.0005940485,0.0001585001,0.001355335,0.003206047,0.009787823,0.797973,0.0007083466,0.0004495165,0.05286615],"study_design_scores_gemma":[0.00001067082,0.00007255947,0.9247536,0.00005343575,0.000071519,0.001461543,0.00171417,0.02253423,0.04586831,0.0003766149,0.003017152,0.00006618167],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913945,0.0002550343,0.006565333,0.00002570374,0.000006309848,0.00002742735,0.000669519,0.0001975979,0.0008587546],"genre_scores_gemma":[0.992109,0.000145687,0.007081278,0.00001088242,0.000004679608,0.00002089082,0.00037611,0.00003435749,0.0002170814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002429237,"threshold_uncertainty_score":0.004830241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04634114629676007,"score_gpt":0.2828722296145251,"score_spread":0.2365310833177651,"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."}}