{"id":"W4298162047","doi":"","title":"Effets de la sélection sur la diversité et la différenciation génétique moléculaire : résultats de simulations et application au pin maritime pour les gènes de la lignification","year":2004,"lang":"fr","type":"preprint","venue":"Prodinra (INRA Bordeaux-Aquitaine)","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Gene; Selection (genetic algorithm); Biology; Trait; Computational biology; Genetics; Gene expression; Evolutionary biology; Quantitative trait locus; Lignin; Botany; Computer science; Artificial intelligence","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":[0.0005265815,0.0005870613,0.0005737345,0.0003400174,0.0005563799,0.0005641903,0.0008283443,0.001189329,0.003007278],"category_scores_gemma":[0.00239896,0.0003262597,0.0006099249,0.0005685827,0.0007002265,0.0004984344,0.0003531873,0.0006833079,0.0002055305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006545905,"about_ca_system_score_gemma":0.0004171615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01489348,"about_ca_topic_score_gemma":0.01098061,"domain_scores_codex":[0.9998957,0.00003072008,0.000004590881,0.00002415887,0.00002388898,0.0000209456],"domain_scores_gemma":[0.997419,0.002171635,0.0001055421,0.00008128422,0.0001405062,0.00008190721],"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":[0.0001937502,0.00008502148,0.004286181,0.000058708,0.00005851906,0.00008454282,0.00005765226,0.9816358,0.008626695,0.0008602837,0.0003065364,0.003746301],"study_design_scores_gemma":[0.00007404766,0.0000760458,0.003100654,0.000004741779,0.0000395536,0.0000253258,0.00004278086,0.987398,0.008128909,0.0008227814,0.0002706145,0.00001660368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804695,0.0003595593,0.01541407,0.0003474624,0.00004512566,0.00001393782,0.0004238102,0.0002810138,0.002645525],"genre_scores_gemma":[0.9929399,0.0001337527,0.005674681,0.00004772125,0.00001140181,0.00002563012,0.0002007474,0.00009291094,0.0008732468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01489348,"threshold_uncertainty_score":0.02961355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01995483026855919,"score_gpt":0.314255529548607,"score_spread":0.2943006992800478,"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."}}