{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006963582,0.0001128468,0.0001143798,0.00003934803,0.0003287818,0.00005727644,0.0001764204,0.00007807395,0.001054136],"category_scores_gemma":[0.00006990365,0.0001183747,0.0001037835,0.0005709869,0.0001194797,0.00007588411,0.00001287817,0.0003073424,0.0004443117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004982385,"about_ca_system_score_gemma":0.00001109929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003007092,"about_ca_topic_score_gemma":0.001032168,"domain_scores_codex":[0.9990175,0.00007187451,0.0001601526,0.0003717637,0.0001968723,0.0001818498],"domain_scores_gemma":[0.9990836,0.000213162,0.00002834561,0.0005287401,0.00001431487,0.0001318021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002582328,0.0004101284,0.003199809,0.000001959633,0.00006017857,0.00002018422,0.0007800753,0.009000487,0.2393549,0.00005072567,0.001280268,0.7458155],"study_design_scores_gemma":[0.001410869,0.0007808096,0.1755727,0.0001478985,0.0003258224,0.0001997878,0.003821346,0.00378357,0.505386,0.02485665,0.2819163,0.001798301],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.872885,0.000025189,0.1146113,0.005419967,0.0001958752,0.000116625,0.00003518844,0.0001798155,0.006531026],"genre_scores_gemma":[0.9614467,0.00005067107,0.03720998,0.0005376644,0.00002492986,0.000003634962,0.00001041131,0.00001750371,0.000698511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7440172,"threshold_uncertainty_score":0.999859,"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."}}