{"id":"W2375991779","doi":"","title":"Study on Tibetan Character Contour Line Extraction Based on Ant Colony Algorithm","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Image and Video Stabilization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Character (mathematics); Computer science; Ant colony optimization algorithms; Artificial intelligence; Line (geometry); Pattern recognition (psychology); Contour line; Skeleton (computer programming); Algorithm; Character recognition; Computer vision; Image (mathematics); Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001777755,0.0002159552,0.0001950703,0.000207346,0.0004164141,0.0001212993,0.0005638808,0.00006833549,0.00001181727],"category_scores_gemma":[0.000001493523,0.0002056146,0.00007656111,0.0004928451,0.00003475379,0.0003016299,0.00007997971,0.0002003289,0.0004062709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009921398,"about_ca_system_score_gemma":0.0000736149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001410658,"about_ca_topic_score_gemma":0.00000310125,"domain_scores_codex":[0.998405,0.00008898415,0.00032832,0.0006404541,0.0002778042,0.0002594087],"domain_scores_gemma":[0.998693,0.0001370217,0.0001419946,0.0007524374,0.0001803882,0.00009511236],"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":[0.00004134744,0.009260075,0.002284745,0.00001893503,0.00006416124,0.0001077281,0.002604492,0.001442328,0.01514221,0.002198525,0.009323576,0.9575119],"study_design_scores_gemma":[0.003720718,0.002168328,0.08707514,0.00004910852,0.00004222451,0.000133606,0.00007179641,0.3929528,0.03245673,0.0003767582,0.4798556,0.001097182],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01008377,0.00001217789,0.9866623,0.0008588646,0.00007375124,0.001457645,0.00001198772,0.0002926459,0.0005468429],"genre_scores_gemma":[0.6707296,0.00001171502,0.3220606,0.004488125,0.0007989379,0.001132236,0.0001067636,0.00004409387,0.0006278837],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9564147,"threshold_uncertainty_score":0.8384718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02740101784521674,"score_gpt":0.2884663153094588,"score_spread":0.2610652974642421,"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."}}