{"id":"W3208031839","doi":"10.5281/zenodo.3946192","title":"Nanc-in-a-Can Canon Generator. SuperCollider code capable of generating and visualizing temporal canons critically and algorithmically","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Generator (circuit theory); Computer science; Programming language; Canon; Code (set theory); Code generation; Computer graphics (images); Art; Operating system; Physics; Key (lock); Set (abstract data type); Literature; Power (physics)","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":[0.0007678308,0.000860359,0.0004019191,0.0006153127,0.000590872,0.00161612,0.001501793,0.0009954675,0.07046653],"category_scores_gemma":[0.00321677,0.0004294088,0.0005495986,0.0003910245,0.0008689637,0.001612709,0.002391318,0.001040929,0.01918939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007236721,"about_ca_system_score_gemma":0.0008203161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001409013,"about_ca_topic_score_gemma":0.002482774,"domain_scores_codex":[0.9996333,0.00005704598,0.00002427515,0.00008714209,0.0001420342,0.00005615835],"domain_scores_gemma":[0.999019,0.0003334871,0.00005923417,0.0003147435,0.0001928225,0.00008077318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002420313,0.0002935897,0.006319363,0.001163141,0.0001099909,0.002050133,0.002656223,0.01194847,0.06230935,0.1639794,0.2573815,0.4893685],"study_design_scores_gemma":[0.0003440683,0.0001902717,0.002335271,0.0002651029,0.00005956048,0.001488192,0.0003889851,0.136498,0.1101007,0.05802451,0.6901526,0.000152672],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01551662,0.0002172955,0.7166228,0.0003929343,0.0003607258,0.0005187807,0.00303098,0.1890586,0.07428125],"genre_scores_gemma":[0.2476657,0.0003997622,0.5158477,0.000898062,0.0001328481,0.001754598,0.009314006,0.08445887,0.1395285],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.07046653,"threshold_uncertainty_score":0.235734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0357335310986141,"score_gpt":0.2996950460750345,"score_spread":0.2639615149764204,"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."}}