{"id":"W4388078265","doi":"10.1242/jeb.246843","title":"ECR Spotlight – Yangfan Zhang","year":2023,"lang":"en","type":"article","venue":"Journal of Experimental Biology","topic":"Physiological and biochemical adaptations","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Zhàng; Diversity (politics); Ecology; Biology; Selection (genetic algorithm); Natural selection; Environmental ethics; Library science; Engineering ethics; Sociology; Political science; Anthropology; Computer science; Engineering; Philosophy; Artificial intelligence; China","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":[0.004896383,0.0009811602,0.0008035724,0.0009190308,0.001883732,0.003777602,0.001010077,0.00324407,0.12876],"category_scores_gemma":[0.01004952,0.0003579886,0.0004060332,0.0005700285,0.0009098398,0.002880519,0.002785055,0.0039661,0.06498498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002373786,"about_ca_system_score_gemma":0.00343936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001502559,"about_ca_topic_score_gemma":0.002182597,"domain_scores_codex":[0.9969832,0.000465693,0.00008966119,0.0007214122,0.001404677,0.0003353714],"domain_scores_gemma":[0.9847823,0.0008108097,0.0003900033,0.0003761536,0.006064683,0.007576171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004445665,0.0000102921,0.00009592111,0.00002617405,0.000002286636,0.0001069714,0.00006456879,0.0000204222,0.0004555718,0.0009542968,0.9868345,0.01138465],"study_design_scores_gemma":[0.000008207305,0.00002130489,0.0003064341,0.00002681915,9.578958e-7,0.000217491,0.0001240719,0.00006268337,0.0001964566,0.0003763505,0.9986482,0.00001103142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.005246446,0.02829338,0.004167754,0.5923373,0.2691597,0.0001815803,0.001797372,0.002183644,0.09663284],"genre_scores_gemma":[0.02680487,0.006582388,0.002140586,0.1007427,0.04087096,0.0002218211,0.001034398,0.001476782,0.8201256],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.12876,"threshold_uncertainty_score":0.4307451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02643062647153238,"score_gpt":0.2877246614096757,"score_spread":0.2612940349381433,"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."}}