{"id":"W2787791500","doi":"10.36510/learnland.v11i1.919","title":"An Exploration of Artistic and Technological Symmetry","year":2018,"lang":"en","type":"article","venue":"LEARNing Landscapes","topic":"Science Education and Perceptions","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coding (social sciences); Computer science; Computational thinking; Heading (navigation); Point (geometry); Reading (process); Software; Visual arts; Mathematics education; Human–computer interaction; Artificial intelligence; Psychology; Sociology; Art; Mathematics; Programming language; Geometry; Engineering; Linguistics; Philosophy; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003676648,0.0003915389,0.0002569104,0.00223821,0.00663534,0.01052284,0.0012938,0.001386687,0.01006501],"category_scores_gemma":[0.004348608,0.000282446,0.0004839974,0.001704766,0.02468601,0.009151933,0.007534829,0.002640573,0.0005765477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00406853,"about_ca_system_score_gemma":0.001989783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00237595,"about_ca_topic_score_gemma":0.003064266,"domain_scores_codex":[0.9964508,0.002220619,0.00006328826,0.0002824554,0.0006020167,0.0003808622],"domain_scores_gemma":[0.997891,0.001262879,0.0001530001,0.0003128517,0.0001668939,0.000213395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001664744,0.0000228615,0.000590308,0.00004695843,0.000003153306,0.0003524799,0.1339757,0.0001721844,0.0004248459,0.8478314,0.001882207,0.01468136],"study_design_scores_gemma":[0.00002694111,0.00006000907,0.002723213,0.0002124964,0.000009176109,0.001263667,0.2599683,0.001337544,0.0007910876,0.3326934,0.4008897,0.00002468528],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1484758,0.00212312,0.01626727,0.01170461,0.0002579922,0.00003933208,0.00004318305,0.0000771669,0.8210115],"genre_scores_gemma":[0.9799752,0.0006018316,0.002853209,0.0003686049,0.00004292743,0.00002559096,0.00002072162,0.00005485007,0.0160571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01052284,"threshold_uncertainty_score":0.03367084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06175506600687014,"score_gpt":0.3756029619572284,"score_spread":0.3138478959503583,"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."}}