{"id":"W3206849198","doi":"10.1145/3478513.3480525","title":"Learning to reconstruct botanical trees from single images","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"King Abdullah University of Science and Technology; Foundation for Food and Agriculture Research; National Science Foundation","keywords":"Tree (set theory); Computer science; Bounding overwatch; Branching (polymer chemistry); Artificial intelligence; Pipeline (software); Tree structure; Pattern recognition (psychology); Algorithm; Mathematics; Binary tree; Combinatorics","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":[0.0003969923,0.0008264655,0.0005118511,0.0007802497,0.0002381011,0.000858195,0.001214721,0.0007830395,0.00180859],"category_scores_gemma":[0.001387105,0.0007814822,0.0007709872,0.0005460154,0.0004978879,0.001443752,0.0008791877,0.001051936,0.0008589739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006075827,"about_ca_system_score_gemma":0.0008399076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004326126,"about_ca_topic_score_gemma":0.01092844,"domain_scores_codex":[0.999711,0.00002389838,0.000009496694,0.0001286035,0.00009837481,0.00002861374],"domain_scores_gemma":[0.9995818,0.0001211082,0.00006736869,0.0001222807,0.00007531865,0.0000322814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008479286,0.00009538155,0.002798405,0.000128351,0.00008629283,0.0001333999,0.0001457496,0.4788907,0.04860276,0.006320115,0.002589202,0.4601249],"study_design_scores_gemma":[0.000003466459,0.00001958425,0.0004934436,0.000008173052,0.000005711111,0.00007012388,0.00001909688,0.9884405,0.006269747,0.00326725,0.001395039,0.000007910482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01986288,0.00009069301,0.9777129,0.00006343341,0.00001561054,0.0000281241,0.0001320574,0.001210601,0.0008837389],"genre_scores_gemma":[0.1967195,0.000211965,0.8001212,0.0000942622,0.00002619824,0.00006275612,0.0007548592,0.0002840234,0.001725306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004326126,"threshold_uncertainty_score":0.008601904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01568083675016028,"score_gpt":0.2361028368479132,"score_spread":0.220422000097753,"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."}}