{"id":"W2291589275","doi":"10.1111/cgf.12809","title":"S<scp>mart</scp>C<scp>anvas</scp>: Context‐inferred Interpretation of Sketches for Preparatory Design Studies","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Sketch; Computer science; Context (archaeology); Abstraction; Object (grammar); Human–computer interaction; Process (computing); Interpretation (philosophy); Set (abstract data type); Engineering drawing; Computer graphics (images); Programming language; Artificial intelligence; Engineering; Algorithm","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":[0.00183074,0.001190095,0.000650769,0.001907996,0.0007782654,0.003806372,0.001494543,0.001259498,0.03819619],"category_scores_gemma":[0.01045113,0.0007642658,0.001024014,0.001095051,0.001223509,0.002368223,0.003520403,0.001261963,0.006935183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000637051,"about_ca_system_score_gemma":0.000735007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002058174,"about_ca_topic_score_gemma":0.004026421,"domain_scores_codex":[0.9987516,0.0004280583,0.00007766284,0.0002585137,0.0004214202,0.00006265387],"domain_scores_gemma":[0.9957421,0.001961834,0.0001771457,0.001277939,0.0006015487,0.0002393379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001034396,0.0001992384,0.003614377,0.001926485,0.0001649386,0.001343705,0.005730852,0.04714004,0.08819107,0.07003239,0.05396949,0.726653],"study_design_scores_gemma":[0.0002736636,0.0002989533,0.004980819,0.000705018,0.0001209508,0.0009568709,0.001720492,0.4573611,0.07051098,0.06164216,0.4011531,0.0002759197],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01506473,0.0004147657,0.9329139,0.0002523168,0.00009971356,0.000297878,0.001372537,0.03458851,0.01499556],"genre_scores_gemma":[0.237766,0.0005920101,0.7451503,0.000133222,0.0000585929,0.0002924289,0.002548318,0.006464045,0.006995226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03819619,"threshold_uncertainty_score":0.1277789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05121712814827403,"score_gpt":0.259856699450648,"score_spread":0.208639571302374,"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."}}