{"id":"W2103242704","doi":"10.1109/iccl.1988.13036","title":"An intentional language as the basis of a 3-D spreadsheet design","year":2003,"lang":"en","type":"article","venue":"","topic":"Spreadsheets and End-User Computing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Variable (mathematics); Extension (predicate logic); Plane (geometry); Basis (linear algebra); Programming language; Space (punctuation); Natural language processing; Artificial intelligence; Mathematics","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":[0.003180941,0.0008551453,0.0004728218,0.00195158,0.001210464,0.00580385,0.002395576,0.001340182,0.01054219],"category_scores_gemma":[0.006473783,0.0008809793,0.00138044,0.001567746,0.00237223,0.005201205,0.002945098,0.002147283,0.004150059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001742342,"about_ca_system_score_gemma":0.002504663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002907054,"about_ca_topic_score_gemma":0.003126292,"domain_scores_codex":[0.9975561,0.00073631,0.0004096471,0.0003001493,0.0008494789,0.0001483505],"domain_scores_gemma":[0.9974801,0.0009217478,0.0001606816,0.000455374,0.0008178769,0.0001643227],"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":[0.00009644637,0.00003039729,0.0003410941,0.0002547701,0.00001822959,0.0002655656,0.001371685,0.006826018,0.00748884,0.9153647,0.01094554,0.05699661],"study_design_scores_gemma":[0.00008128473,0.0001072903,0.0002120676,0.0003098616,0.00005445984,0.0007146745,0.0003887478,0.1054115,0.02250944,0.1959444,0.6741493,0.0001169255],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001295622,0.00005197412,0.9895197,0.0002055475,0.00005745855,0.0001158454,0.000162801,0.002328885,0.006262144],"genre_scores_gemma":[0.0266541,0.0001799237,0.9610845,0.000266061,0.0000399578,0.0004286951,0.0005506076,0.0009780835,0.009818058],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01054219,"threshold_uncertainty_score":0.03526711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223501564178398,"score_gpt":0.2683392496287693,"score_spread":0.2461042339869853,"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."}}