{"id":"W4407989241","doi":"10.15485/2507279","title":"Data from TropiRoot 1.0 database: tropical root characteristics across environments","year":2025,"lang":"en","type":"article","venue":"","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Root (linguistics); Database; Geography; Computer science","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":[0.001234707,0.001344132,0.001359455,0.008107634,0.0005025474,0.002249579,0.001718465,0.0007919574,0.02949066],"category_scores_gemma":[0.008678283,0.0005813443,0.0009603675,0.0112342,0.000256191,0.002176781,0.002138152,0.0009306069,0.02595406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008210146,"about_ca_system_score_gemma":0.001829991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01517178,"about_ca_topic_score_gemma":0.01868309,"domain_scores_codex":[0.9983578,0.000143531,0.0004859592,0.0003745361,0.0004763981,0.0001616938],"domain_scores_gemma":[0.9941844,0.001169378,0.001088262,0.0009480173,0.002153815,0.0004561722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006905987,0.0001265144,0.03167377,0.006300946,0.000208474,0.0003152674,0.0007355512,0.00167271,0.00419703,0.003101376,0.8999427,0.05103504],"study_design_scores_gemma":[0.0001712713,0.00006176606,0.06810058,0.0007093812,0.0001266029,0.0003457192,0.0005283129,0.001553281,0.002019801,0.00177431,0.9244735,0.0001354781],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002327878,0.0001658396,0.0006702307,0.00003888871,0.00001303242,0.00003394797,0.9945812,0.0009825707,0.001186427],"genre_scores_gemma":[0.003613692,0.000166894,0.001944387,0.00003186096,0.000009212827,0.0001553879,0.9932922,0.0002940121,0.0004922663],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02949066,"threshold_uncertainty_score":0.09865606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04241585667613865,"score_gpt":0.2687875827059913,"score_spread":0.2263717260298527,"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."}}