{"id":"W6981102697","doi":"","title":"Development of optimal breeding zones for white spruce in Ontario under current, past, and anticipated future climate change / by Ashley Marie Thomson.","year":2017,"lang":"en","type":"dissertation","venue":"Knowledge Commons (Lakehead University)","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Principal component analysis; Phenology; Climate change; Sowing; Best linear unbiased prediction; Regression; Field trial; Precipitation; Taiga; Selection (genetic algorithm)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000275774,0.0001366849,0.0001044177,0.0002826006,0.0008603274,0.0007309623,0.0003156039,0.000122257,0.001640816],"category_scores_gemma":[0.0002640439,0.0001051481,0.0001199,0.0002711556,0.0003623803,0.0001384901,0.000286502,0.0001514512,0.0003584746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004453681,"about_ca_system_score_gemma":0.004510955,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7668586,"about_ca_topic_score_gemma":0.966743,"domain_scores_codex":[0.9999071,0.000009384504,0.000003670951,0.00003184452,0.00003116947,0.00001676382],"domain_scores_gemma":[0.9998347,0.00001633671,0.00004254709,0.000007113209,0.00006032813,0.00003903589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000462769,0.0001587824,0.5319693,0.0003431369,0.00004555723,0.0006435892,0.005212411,0.003421135,0.1440111,0.001295768,0.02268644,0.28975],"study_design_scores_gemma":[0.00001074993,0.00004722833,0.9818631,0.00003979574,0.0000116275,0.00005768129,0.0009680367,0.0007745812,0.001074837,0.0000770637,0.01506515,0.00001022936],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783543,0.002001666,0.001484703,0.0004749043,0.00002749765,0.00009770822,0.001116134,0.00006540256,0.01637776],"genre_scores_gemma":[0.9689745,0.001601421,0.009315377,0.0001456052,0.00001176503,0.00007145682,0.001629419,0.00006110696,0.01818942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2331414,"threshold_uncertainty_score":0.4690288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09605711260986008,"score_gpt":0.3326085283566922,"score_spread":0.2365514157468322,"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."}}