{"id":"W1785947234","doi":"10.1139/x11-027","title":"Comparing selection system and diameter-limit cutting in uneven-aged northern hardwoods using computer simulation","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Silviculture; Clearcutting; Selection (genetic algorithm); Limit (mathematics); Mathematics; Maple; Forest management; Environmental science; Statistics; Forestry; Botany; Biology; Computer science; Agroforestry; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001333373,0.00008079318,0.0001385508,0.0004872399,0.0002376593,0.00008518502,0.0001887066,0.00004703446,0.0001287349],"category_scores_gemma":[0.0000484368,0.00007743946,0.00003075807,0.0004756805,0.0001439637,0.0003246415,0.00005481919,0.0003220947,0.00003411017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006956295,"about_ca_system_score_gemma":0.000092469,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08959411,"about_ca_topic_score_gemma":0.4369537,"domain_scores_codex":[0.998735,0.0001863074,0.0002707333,0.0001284011,0.0002637182,0.0004158531],"domain_scores_gemma":[0.9994065,0.00006567919,0.00009744395,0.00008565331,0.00003918091,0.0003055402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001225486,0.000006710423,0.9229535,0.00001900756,0.000007883739,0.0000507361,0.001201613,0.07401674,0.00002295547,0.00006958315,0.00006970872,0.001569344],"study_design_scores_gemma":[0.0002430031,0.00009348087,0.7750824,0.0001000095,0.000005274539,0.00002694067,0.00008971368,0.2239452,0.00001366941,0.00007579484,0.0002552128,0.0000693407],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960173,0.00002514346,0.0007864146,0.00002129223,0.00008045329,0.0001375679,5.749874e-7,0.000003861723,0.002927426],"genre_scores_gemma":[0.9983637,0.000001436213,0.001435764,0.000009893427,0.0001033712,9.999476e-7,5.99573e-7,0.00001230949,0.00007190872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3473595,"threshold_uncertainty_score":0.9164684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172369044281047,"score_gpt":0.3100186975723739,"score_spread":0.1927817931442692,"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."}}