{"id":"W3122855612","doi":"10.4204/eptcs.333.7","title":"The more legs the merrier: A new composition for symmetric (multi-)lenses","year":2021,"lang":"en","type":"article","venue":"Electronic Proceedings in Theoretical Computer Science","topic":"Web Applications and Data Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"Australian Research Council; Mount Allison University","keywords":"Lens (geology); Composition (language); Mathematics; Variety (cybernetics); Pure mathematics; Computer science; Combinatorics; Physics; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001220491,0.000767676,0.0004505247,0.0009526926,0.001669779,0.002767123,0.000955782,0.001031912,0.01103971],"category_scores_gemma":[0.002284605,0.0004995486,0.001380656,0.0008876315,0.003171012,0.007487108,0.00349079,0.001669975,0.00197171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001162666,"about_ca_system_score_gemma":0.0006760403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001275925,"about_ca_topic_score_gemma":0.001197336,"domain_scores_codex":[0.9983895,0.0003711611,0.00009372508,0.0003719092,0.0005813695,0.0001924],"domain_scores_gemma":[0.9991149,0.0001568598,0.0001004821,0.0003145529,0.0001862435,0.0001268448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001051019,0.00003219255,0.0004702396,0.00008479449,0.00001581642,0.0004457781,0.0007762228,0.004162653,0.00934986,0.9392245,0.001142785,0.04419],"study_design_scores_gemma":[0.0000407911,0.0002339976,0.0006679036,0.0001119667,0.00005892899,0.001501268,0.0008817694,0.05670265,0.0192332,0.7679271,0.1525688,0.00007164641],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04575194,0.0004024817,0.8961551,0.0005626618,0.0002452,0.00009325968,0.00009291719,0.0007939072,0.05590253],"genre_scores_gemma":[0.4627032,0.0005328884,0.4925901,0.0003225254,0.000194693,0.0001133787,0.000210174,0.0007316888,0.04260134],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01103971,"threshold_uncertainty_score":0.03693151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00948605200614814,"score_gpt":0.2640331341295555,"score_spread":0.2545470821234073,"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."}}