{"id":"W2085837697","doi":"10.5558/tfc83754-5","title":"Mise au point d'un tarif de cubage général pour les forêts québécoises : une approche pour mieux évaluer l'incertitude associée aux prévisions","year":2007,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest ecology and management","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts (Québec)","funders":"","keywords":"Statistics; Mathematics; Plot (graphics); Volume (thermodynamics); Forestry; Econometrics; Geography; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009977769,0.0002632727,0.0002025184,0.00003511745,0.0007913916,0.00003662621,0.0007691754,0.000167778,0.006394519],"category_scores_gemma":[0.0001566568,0.0001998862,0.0001909161,0.0002448914,0.0005425491,0.0002144431,0.0005808105,0.0003758237,0.001098585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000951306,"about_ca_system_score_gemma":0.0001900304,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.008529997,"about_ca_topic_score_gemma":0.03793524,"domain_scores_codex":[0.9978222,0.00009049701,0.0003352036,0.0004209849,0.0003377265,0.0009934171],"domain_scores_gemma":[0.9988037,0.0002478054,0.0001555628,0.0005756254,0.00001309939,0.0002041667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004539162,0.002252934,0.3692028,0.0001123672,0.0005213937,0.000342424,0.007312924,0.02591342,0.007504192,0.02209947,0.5275036,0.03678057],"study_design_scores_gemma":[0.001071458,0.0001511817,0.9280267,0.00003010055,0.0001072517,0.00003561852,0.0009645202,0.002682274,0.002827976,0.03480727,0.02892941,0.0003662028],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546398,0.00008438481,0.004577834,0.006186357,0.0001600516,0.0005307158,0.00002211683,0.0001295834,0.03366918],"genre_scores_gemma":[0.9890794,0.00001956379,0.002565224,0.000873421,0.0001964169,0.00006423721,0.00002389636,0.00003523443,0.007142654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5588239,"threshold_uncertainty_score":0.9996791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564280356496566,"score_gpt":0.2590161283065857,"score_spread":0.24337332474162,"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."}}