{"id":"W2078250802","doi":"10.1093/forestry/cpu045","title":"Value-adding through silvicultural flexibility: an operational level simulation study","year":2014,"lang":"en","type":"article","venue":"Forestry An International Journal of Forest Research","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flexibility (engineering); Value (mathematics); Statistics; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003065897,0.0001783502,0.0001886526,0.0002078437,0.000355148,0.0004052348,0.001386891,0.00008379952,0.001777361],"category_scores_gemma":[0.0006019316,0.0001419017,0.0001049031,0.0003136338,0.0002835819,0.003517854,0.0003673988,0.0005239962,0.0002998174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003384988,"about_ca_system_score_gemma":0.00005723494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009801253,"about_ca_topic_score_gemma":0.0003464451,"domain_scores_codex":[0.9955435,0.0005803946,0.0006016623,0.0003421077,0.002537971,0.000394405],"domain_scores_gemma":[0.9985657,0.0002566931,0.0002169597,0.0003490506,0.0003903971,0.0002211561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003019516,0.0008256772,0.5204225,0.000004082459,0.00006126348,0.00002807526,0.001711744,0.4587603,0.00008387367,0.0149654,0.0007578182,0.002077369],"study_design_scores_gemma":[0.001346882,0.002086186,0.8180928,0.00003197787,0.00001620916,0.00003660877,0.0004318529,0.1512346,0.00005536648,0.01426138,0.01219108,0.0002151261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888784,0.000003264948,0.001300686,0.0003809137,0.0003930358,0.0003720996,0.0000106894,0.0000183782,0.008642538],"genre_scores_gemma":[0.9948274,0.00000387655,0.002294729,0.0001483697,0.001293401,0.00001319908,0.00005305816,0.00001977892,0.001346125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3075257,"threshold_uncertainty_score":0.9991351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1667367031998402,"score_gpt":0.4512857727030488,"score_spread":0.2845490695032086,"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."}}