{"id":"W3015291456","doi":"10.17504/protocols.io.baaciaaw","title":"Tree Mapping for Leaf Collection (Megantic Only) v1","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Crew; Observatory; Tree (set theory); Geography; Forestry; Computer science; Remote sensing; Mathematics; Physics; Astronomy; Archaeology; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001106911,0.0008610595,0.0007026547,0.00236632,0.001180614,0.001660477,0.001617892,0.0006860577,0.1269928],"category_scores_gemma":[0.002861322,0.0007014848,0.0004846261,0.002752666,0.0002845345,0.001277392,0.002360898,0.0007498529,0.07895556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000880584,"about_ca_system_score_gemma":0.002906688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05221858,"about_ca_topic_score_gemma":0.1604734,"domain_scores_codex":[0.9990914,0.00005939018,0.00005055573,0.000224571,0.0003815999,0.0001925903],"domain_scores_gemma":[0.9980327,0.0001276501,0.00008965386,0.0008120895,0.0007144152,0.0002233035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003229372,0.00007346862,0.005784666,0.0004869885,0.00005897782,0.0002420566,0.000786575,0.0006585449,0.02710292,0.003453251,0.8393143,0.1217154],"study_design_scores_gemma":[0.0001038087,0.000050394,0.04546522,0.0001520718,0.00002650471,0.0002536306,0.0002609734,0.00302727,0.01175978,0.002734163,0.9361086,0.00005746784],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02018743,0.0003934965,0.1128687,0.0002975225,0.0004079778,0.0022051,0.6803231,0.08277486,0.1005419],"genre_scores_gemma":[0.04435738,0.0002649743,0.2115881,0.0003362336,0.0001253829,0.004065811,0.6580377,0.02723134,0.05399314],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1269928,"threshold_uncertainty_score":0.4248333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04642638039584285,"score_gpt":0.2688220607026362,"score_spread":0.2223956803067934,"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."}}