{"id":"W1996503485","doi":"10.1002/cav.26","title":"Physically‐based simulation of plant leaf growth","year":2004,"lang":"en","type":"article","venue":"Computer Animation and Virtual Worlds","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Plant growth; Process (computing); Computer science; Growth rate; Computer simulation; Set (abstract data type); Compressibility; Animation; Biological system; Mechanics; Simulation; Mathematics; Geometry; Botany; Physics; Biology; Computer graphics (images)","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":[],"consensus_categories":[],"category_scores_codex":[0.00005905687,0.00007445858,0.0001157528,0.00001606813,0.0000807677,0.00001640953,0.0000782996,0.00005715815,0.00003733608],"category_scores_gemma":[0.000007465112,0.00003288861,0.00003634015,0.0001401039,0.00005065054,0.00007700689,0.00002636311,0.00005556193,0.00001136119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007387351,"about_ca_system_score_gemma":0.000003256724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001137688,"about_ca_topic_score_gemma":0.00004427143,"domain_scores_codex":[0.9995397,0.00001830509,0.0001378814,0.0001303462,0.00008203246,0.00009176478],"domain_scores_gemma":[0.9997478,0.00008950051,0.00006101465,0.00002821101,0.00004334344,0.00003013949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004722138,0.001082618,0.01045298,0.00007186822,0.00007482171,0.000009459034,0.0005609615,0.02974043,0.3394117,0.2050946,0.0004838484,0.4125445],"study_design_scores_gemma":[0.003152954,0.003109653,0.5752726,0.0001623975,0.00005245779,0.000006326455,0.000148712,0.3883151,0.01620281,0.01067937,0.002293578,0.0006040484],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874195,0.00001747262,0.01130536,0.0009004178,0.00003913434,0.00009990495,0.00001908366,0.0001073391,0.00009176884],"genre_scores_gemma":[0.9992856,0.000004170991,0.0002668905,0.0003229959,0.00006359438,0.000003005131,0.00004386172,5.762753e-7,0.000009286385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5648196,"threshold_uncertainty_score":0.1341159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461254720692339,"score_gpt":0.2155773819349752,"score_spread":0.2009648347280518,"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."}}