{"id":"W4415034541","doi":"10.1109/netact65906.2025.11187837","title":"A Deep Learning Framework for Virtual Drawing and Geometric Shape Prediction Using Convolutional Neural Networks","year":2025,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Softmax function; Convolutional neural network; Deep learning; Set (abstract data type); Backpropagation; Artificial neural network; Test set; Pattern recognition (psychology)","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":[0.0003696664,0.001028876,0.0005127721,0.0004868365,0.0002802855,0.0007043308,0.001757225,0.0008782228,0.00280836],"category_scores_gemma":[0.0006866427,0.0005581203,0.000749198,0.0006316277,0.0004099698,0.0008508008,0.0008232653,0.001331172,0.0009893879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187176,"about_ca_system_score_gemma":0.001161991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02228933,"about_ca_topic_score_gemma":0.0296365,"domain_scores_codex":[0.9998092,0.00002252042,0.000009148354,0.00005875024,0.00006430582,0.00003598519],"domain_scores_gemma":[0.9998612,0.00003692532,0.00001603523,0.00002088819,0.00005175998,0.00001311807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000768512,0.00007814992,0.0005569733,0.00008048186,0.00007470479,0.00009646316,0.00002734088,0.7550125,0.008971409,0.01004432,0.004217173,0.2207636],"study_design_scores_gemma":[0.000002232002,0.00001122379,0.00007441372,0.000003852495,0.000003973823,0.00001073959,0.000001619397,0.9966085,0.001071565,0.001497891,0.0007110059,0.000003026183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008050652,0.0004914247,0.9873985,0.0001634159,0.00005221496,0.00003394881,0.0002282941,0.001846022,0.00173544],"genre_scores_gemma":[0.4560828,0.001200482,0.5246072,0.0003509375,0.0001061451,0.0003065113,0.001912694,0.00024773,0.0151855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02228933,"threshold_uncertainty_score":0.04431921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00953940690238818,"score_gpt":0.2238910321664921,"score_spread":0.214351625264104,"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."}}