{"id":"W1890979602","doi":"10.1002/9781118854396.ch15","title":"Using Genomic Approaches to Unlock the Potential of CWR for Crop Adaptation to Climate Change","year":2015,"lang":"en","type":"other","venue":"","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adaptation (eye); Climate change; Crop; Biology; Ecology; Neuroscience","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":[0.001043638,0.0004749849,0.0004100755,0.0008683284,0.0004306501,0.001713428,0.0009633583,0.00102868,0.01175072],"category_scores_gemma":[0.0007999372,0.0002280922,0.0005579779,0.001210823,0.000808518,0.001615808,0.00183749,0.002228218,0.001899808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009344531,"about_ca_system_score_gemma":0.0008096683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002245906,"about_ca_topic_score_gemma":0.00503302,"domain_scores_codex":[0.9997649,0.00003622652,0.00001132402,0.0000996781,0.00004931827,0.00003861335],"domain_scores_gemma":[0.999692,0.0001180111,0.00005503039,0.00005714168,0.00002764567,0.00005018709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003976021,0.0001573645,0.006407262,0.0006229602,0.000149036,0.0005824106,0.0003594944,0.002656415,0.4706919,0.1190698,0.006182733,0.3927231],"study_design_scores_gemma":[0.000192314,0.0004514724,0.09110503,0.0006035374,0.0004995728,0.001192931,0.00100722,0.01332267,0.10052,0.1984974,0.5924239,0.0001838638],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.3187142,0.03231178,0.2992421,0.01635068,0.00207183,0.0003156523,0.009412813,0.003503642,0.3180773],"genre_scores_gemma":[0.732255,0.02617939,0.1595048,0.006570912,0.0006242565,0.0002061153,0.01022133,0.001044562,0.0633937],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01175072,"threshold_uncertainty_score":0.0393101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4097844316267624,"score_gpt":0.2567008047581775,"score_spread":0.1530836268685849,"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."}}