{"id":"W2062428634","doi":"10.3102/0013189x035005003","title":"Curriculum-Based Ecosystems: Supporting Knowing From an Ecological Perspective","year":2006,"lang":"en","type":"article","venue":"Educational Researcher","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":295,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Affordance; Perspective (graphical); Ecological psychology; Computer science; Curriculum; Point (geometry); Psychology; Ecology; Sociology; Human–computer interaction; Cognitive science; Artificial intelligence; Cognitive psychology; Pedagogy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003928677,0.0001411186,0.0001693064,0.0002009181,0.0003169591,0.00008089596,0.0002750531,0.000138606,0.02725313],"category_scores_gemma":[0.002170959,0.0001257172,0.00007272024,0.0003776302,0.0001160712,0.0001032287,0.00003074002,0.0008039439,0.0007391592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004409576,"about_ca_system_score_gemma":0.0004742461,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02342893,"about_ca_topic_score_gemma":0.0003996584,"domain_scores_codex":[0.9954355,0.002866772,0.0003010689,0.0005143603,0.000397101,0.000485232],"domain_scores_gemma":[0.9976887,0.001296761,0.000125428,0.0002981074,0.0004832742,0.0001077726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004627173,0.003194423,0.7163851,0.000009984659,0.00007768956,0.0000195716,0.004639244,0.0001441208,0.0009245457,0.1992966,0.07264572,0.002616659],"study_design_scores_gemma":[0.000423745,0.0001354694,0.9486117,0.00002429487,0.00000787186,0.000003517242,0.008853191,0.001294427,0.0000485835,0.0117493,0.02863196,0.000215952],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9008554,0.0001557123,0.001680116,0.006050213,0.0007549434,0.0001924361,0.00002189083,0.00008206732,0.09020725],"genre_scores_gemma":[0.9812883,1.21348e-7,0.005668889,0.0002037775,0.002695554,0.0001218303,0.000332215,0.00002808746,0.009661218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2322265,"threshold_uncertainty_score":0.9830741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08621328131763206,"score_gpt":0.5035070395352017,"score_spread":0.4172937582175696,"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."}}