{"id":"W6929636966","doi":"10.5063/q81bgh","title":"York University Tree Inventory","year":2019,"lang":"en","type":"dataset","venue":"UC Santa Barbara","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Census; Tree (set theory); Block (permutation group theory); Metropolitan area; Geographic coordinate system; Table (database); University campus","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000268022,0.0003125231,0.0006285368,0.000290781,0.00008764579,0.00002717166,0.00042341,0.0003745673,0.001609391],"category_scores_gemma":[0.0001896393,0.0002937352,0.0002308412,0.0002071893,0.0001516344,0.00004716299,0.000173463,0.001458208,0.001448693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002051591,"about_ca_system_score_gemma":0.0003442458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004005961,"about_ca_topic_score_gemma":0.00001985381,"domain_scores_codex":[0.9983491,0.00009478551,0.0002340052,0.0004996764,0.0004471501,0.0003752765],"domain_scores_gemma":[0.9985266,0.00008853364,0.0001605472,0.0008693186,0.00003899356,0.000316017],"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":[0.0000822982,0.00008290847,0.0009479842,0.0003262034,0.0001309206,0.000479584,0.00002440851,0.000002873419,0.00003582703,0.00001314133,0.9959897,0.001884184],"study_design_scores_gemma":[0.001224171,0.0001252228,0.001066761,0.0003971671,0.0004568757,0.0001064498,0.0000595,0.0004871691,0.000003794262,0.000008808581,0.9957775,0.0002865908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002121001,0.001606501,0.00004035019,0.000947881,0.002042749,0.0005078153,0.9844543,0.0001105167,0.008168833],"genre_scores_gemma":[0.0003497477,0.00103665,0.0001847416,0.001994717,0.000802102,0.0000012532,0.9905137,0.00004056112,0.005076488],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006059387,"threshold_uncertainty_score":0.9999515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862240799480356,"score_gpt":0.2720323660076589,"score_spread":0.2534099580128553,"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."}}