{"id":"W2117365907","doi":"10.1051/forest:2002043","title":"Optimization of multiple trait selection in western hemlock(<i>Tsuga heterophylla</i> (Raf.) Sarg.) including pulpand paper properties","year":2002,"lang":"en","type":"article","venue":"Annals of Forest Science","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Western Hemlock; Pulp (tooth); Tsuga; Selection (genetic algorithm); Tree breeding; Trait; Agricultural engineering; Computer science; Biology; Engineering; Botany; Woody plant; Machine learning; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001719531,0.0001250307,0.0001802637,0.0002119169,0.00008160347,0.00003417609,0.0001808542,0.00004265795,0.00002866902],"category_scores_gemma":[0.00005254492,0.000101538,0.00004003926,0.0005848695,0.000190446,0.0007710171,0.00003270695,0.00006198553,0.000003564501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002900269,"about_ca_system_score_gemma":0.00001219457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000141724,"about_ca_topic_score_gemma":0.000252962,"domain_scores_codex":[0.9990239,0.00001520402,0.0002840954,0.0001667836,0.0002488005,0.0002611895],"domain_scores_gemma":[0.9996724,0.00001903046,0.00005753219,0.0001042823,0.0001031357,0.00004359931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002202764,0.00007795214,0.07629361,0.0001041438,0.00001218715,9.044886e-7,0.001626526,0.8577896,0.06167762,0.00002098121,0.00003466949,0.002339715],"study_design_scores_gemma":[0.0005532302,0.0003142516,0.04256395,0.000259061,0.00000932268,0.000005870462,0.00008798874,0.5672289,0.3884395,0.00007680749,0.0001936978,0.0002674429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978102,0.0008956213,0.0003279428,0.0001003862,0.00005976552,0.0001623088,0.000003339577,0.00004922523,0.0005911461],"genre_scores_gemma":[0.9990445,0.000243308,0.000557793,0.00002424457,0.00001834853,0.00001470047,0.000001043702,0.00001319614,0.00008289071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3267619,"threshold_uncertainty_score":0.4140601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07508631941482768,"score_gpt":0.2491546573745121,"score_spread":0.1740683379596845,"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."}}