{"id":"W2791202176","doi":"10.1111/nph.15009","title":"A new method for the rapid characterization of root growth and distribution using digital image correlation","year":2018,"lang":"en","type":"article","venue":"New Phytologist","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital image correlation; Biological system; Root (linguistics); Computer science; Tracing; Biology; Materials science","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":[0.00120279,0.0009170635,0.0007121718,0.00345987,0.0005043746,0.0009265728,0.0009267181,0.0007776716,0.002929803],"category_scores_gemma":[0.002592256,0.0006770222,0.0004921385,0.002356129,0.0006630398,0.001291121,0.001325246,0.001480061,0.0011918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007807747,"about_ca_system_score_gemma":0.001036117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001688688,"about_ca_topic_score_gemma":0.0032457,"domain_scores_codex":[0.9985554,0.0001330986,0.00008974908,0.0003792219,0.0007569203,0.00008558364],"domain_scores_gemma":[0.9976005,0.0006144258,0.0002808002,0.0005248841,0.0008750443,0.0001043372],"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":[0.0001052864,0.00006138594,0.002533647,0.0005183865,0.00007975677,0.0001811419,0.0002131977,0.001828176,0.7446539,0.005535563,0.005969196,0.2383203],"study_design_scores_gemma":[0.00007236223,0.0003203477,0.01462126,0.0001005041,0.0001508597,0.003136062,0.0001619416,0.1869884,0.7156301,0.004104508,0.07440145,0.0003123377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01325496,0.0006085655,0.9802651,0.000182813,0.0001607379,0.0001643977,0.000697169,0.002459564,0.002206682],"genre_scores_gemma":[0.05056089,0.0005413131,0.9457706,0.0001237516,0.00006004005,0.0003714172,0.0004559685,0.0002026261,0.001913464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00345987,"threshold_uncertainty_score":0.009801209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587709279113674,"score_gpt":0.2599358821014865,"score_spread":0.2340587893103498,"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."}}