{"id":"W1489114095","doi":"10.1023/a:1013706806865","title":"An Inverse Gaussian distribution of tree frequencies based on tree size","year":2002,"lang":"en","type":"article","venue":"Environmental and Ecological Statistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Forest Service","funders":"","keywords":"Poisson distribution; Tree (set theory); Mathematics; Statistics; Distribution (mathematics); Plot (graphics); Econometrics; Forestry; Geography; Combinatorics; Mathematical analysis","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":[0.007194373,0.0004969668,0.0008403331,0.003047984,0.0007479324,0.001732534,0.002035127,0.001671077,0.003462574],"category_scores_gemma":[0.04909635,0.0006355222,0.00135838,0.003323042,0.002794266,0.002832616,0.001409512,0.002116044,0.001419844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001191868,"about_ca_system_score_gemma":0.001148334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00508117,"about_ca_topic_score_gemma":0.003839298,"domain_scores_codex":[0.9966583,0.0009553143,0.0001372618,0.001087275,0.0008484256,0.0003133857],"domain_scores_gemma":[0.976157,0.01488109,0.001572971,0.004062535,0.00275961,0.0005668302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0009588487,0.0003179833,0.06411655,0.000534395,0.0004064477,0.0007508193,0.003205177,0.225069,0.03754512,0.3961441,0.0147606,0.2561909],"study_design_scores_gemma":[0.00008027263,0.0001882991,0.0370226,0.0001437592,0.0001467097,0.001751421,0.0003303829,0.7973863,0.005573686,0.1465861,0.01060411,0.0001862455],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08748996,0.0003232867,0.9083242,0.0002663924,0.0001085013,0.00009040411,0.000438951,0.0009673315,0.001991019],"genre_scores_gemma":[0.8138385,0.0009169183,0.174221,0.0004166262,0.0003863322,0.0003449502,0.002463616,0.0006471056,0.006764858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007194373,"threshold_uncertainty_score":0.03804791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378580585769571,"score_gpt":0.1976434632864014,"score_spread":0.1838576574287057,"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."}}