{"id":"W2104135958","doi":"10.1007/s00468-012-0731-6","title":"Measuring whole-plant transpiration gravimetrically: a scalable automated system built from components","year":2012,"lang":"en","type":"article","venue":"Trees","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Transpiration; Modular design; Scalability; Software; Flexibility (engineering); Computer science; Environmental science; Statistics; Operating system; Mathematics; Botany","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001434671,0.0001104285,0.0001287579,0.00004676644,0.0001051649,0.00003415299,0.0001337096,0.00006622525,0.00008809148],"category_scores_gemma":[0.000004143701,0.00009322321,0.00003849374,0.0002114941,0.00002888131,0.0002547629,0.0000337596,0.00007105128,0.0008138066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000150834,"about_ca_system_score_gemma":0.00000230266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001577764,"about_ca_topic_score_gemma":0.0002154016,"domain_scores_codex":[0.999068,0.00005046353,0.0001870477,0.0001547679,0.0002880834,0.0002517024],"domain_scores_gemma":[0.9996488,0.00002704509,0.00005293775,0.0001539052,0.000003570019,0.0001137406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002826001,0.0002364275,0.8437937,0.00001525183,0.00004979389,0.00001141707,0.0006262697,0.01552032,0.1369828,0.000186918,0.000402002,0.002146813],"study_design_scores_gemma":[0.0003817213,0.00001824528,0.5711676,0.0000676895,0.00004867694,0.0000130806,0.00002224058,0.423949,0.001800461,0.00003330327,0.002290075,0.0002078979],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949945,0.00009795748,0.001179685,0.00002935067,0.0001338524,0.0001178562,0.000129606,0.0003414857,0.002975727],"genre_scores_gemma":[0.9986432,0.000004238251,0.0008742479,0.00001708644,0.00003005721,0.000009756081,0.0002381654,0.00001069313,0.0001725312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4084287,"threshold_uncertainty_score":0.9999642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03025139870369292,"score_gpt":0.2049084004823499,"score_spread":0.174657001778657,"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."}}