{"id":"W2909275901","doi":"10.1139/cjfr-2018-0213","title":"A new method to estimate clumping index integrating gap fraction averaging with the analysis of gap size distribution","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Statistics; Fraction (chemistry); Leaf area index; Chemistry; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007329377,0.0007542407,0.0006665355,0.002731002,0.0003390295,0.0005882179,0.0008704193,0.0004343963,0.0008131256],"category_scores_gemma":[0.002360741,0.0003195998,0.0005133721,0.001592802,0.0002763351,0.001324844,0.0006663053,0.0005139518,0.0004686304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000298036,"about_ca_system_score_gemma":0.0004018002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001925948,"about_ca_topic_score_gemma":0.002566198,"domain_scores_codex":[0.9992151,0.00011036,0.00005011256,0.0002517739,0.0003334985,0.00003900456],"domain_scores_gemma":[0.9987639,0.0003957208,0.0002250034,0.0001457014,0.0004185504,0.00005117973],"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":[0.0002021673,0.0001240474,0.04549488,0.0004695566,0.0002181986,0.0001944888,0.0003418903,0.01062188,0.1046216,0.002069271,0.002276513,0.8333654],"study_design_scores_gemma":[0.0000960519,0.0005922602,0.1502392,0.00009780988,0.0004255537,0.002751642,0.0002805674,0.7379383,0.08501856,0.004759518,0.01742697,0.000373537],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06371351,0.000877396,0.9325282,0.00003905466,0.0001314712,0.000110205,0.0002531673,0.001222057,0.001124943],"genre_scores_gemma":[0.2813155,0.0004580609,0.715836,0.0000608712,0.0001032827,0.0002635833,0.0004626822,0.0002187224,0.001281294],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002731002,"threshold_uncertainty_score":0.003876209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428939712211448,"score_gpt":0.3468754727099385,"score_spread":0.322586075587824,"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."}}