{"id":"W1559955887","doi":"","title":"Genetic Diversity as Inspiration for Instructional Design","year":2004,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Science Education and Perceptions","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Roads University","funders":"","keywords":"Diversity (politics); Computer science; Biology; Sociology; Anthropology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004730184,0.0002453085,0.0002206835,0.000266406,0.000816308,0.0001425036,0.0002205484,0.0001590066,0.002361264],"category_scores_gemma":[0.00006612692,0.000271698,0.00004855231,0.0006306702,0.0001566545,0.0002634973,0.00005426097,0.000486364,0.0002795708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007133889,"about_ca_system_score_gemma":0.001041028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00203916,"about_ca_topic_score_gemma":0.0008680327,"domain_scores_codex":[0.9977214,0.0002892601,0.000404835,0.0006926175,0.00049028,0.000401649],"domain_scores_gemma":[0.9986584,0.0001277467,0.0004874945,0.000269478,0.000205492,0.0002513742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000435091,0.0009057569,0.197129,0.00006400511,0.00002724844,0.000002329829,0.006757994,0.0008035385,0.0002000085,0.714206,0.002964327,0.07650466],"study_design_scores_gemma":[0.00104117,0.0006369183,0.9342158,0.0001051084,0.00001591639,0.00001083672,0.003406047,0.00005942272,0.00001792262,0.03678668,0.0233727,0.000331433],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9195551,0.0002139037,0.002256769,0.03190676,0.005820025,0.001524683,0.00002396272,0.0001581771,0.03854068],"genre_scores_gemma":[0.9581919,0.0001074086,0.003445328,0.002451965,0.000414168,0.0003072303,0.00004805666,0.00002425094,0.03500972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7370868,"threshold_uncertainty_score":0.9999735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1799530519234805,"score_gpt":0.3590231311972139,"score_spread":0.1790700792737334,"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."}}