{"id":"W4404636187","doi":"10.3390/s24237458","title":"An Automated Feature-Based Image Registration Strategy for Tool Condition Monitoring in CNC Machine Applications","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Tool wear; Artificial intelligence; Computer science; Computer vision; Machine tool; Feature (linguistics); Machine vision; Subpixel rendering; Image processing; Machining; Process (computing); Enhanced Data Rates for GSM Evolution; Engineering; Image (mathematics); Pixel; Mechanical engineering","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":[0.0008924821,0.0005708931,0.0006702058,0.001732932,0.0002989894,0.0008161963,0.001195201,0.000725251,0.001514277],"category_scores_gemma":[0.002657009,0.000287346,0.0003248868,0.001436925,0.0003997308,0.0009504461,0.0008740636,0.000676338,0.001193457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004845606,"about_ca_system_score_gemma":0.0008775798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001621626,"about_ca_topic_score_gemma":0.002752643,"domain_scores_codex":[0.9987137,0.0001411583,0.00005923053,0.0002867362,0.0007025705,0.00009659676],"domain_scores_gemma":[0.9987882,0.0001708476,0.0001864841,0.0003117995,0.0005032162,0.00003955091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003035252,0.0001626697,0.002655581,0.0002198692,0.00003186559,0.0001818776,0.0002035022,0.00991355,0.3128905,0.001758918,0.003217803,0.6684602],"study_design_scores_gemma":[0.00004850224,0.0008521681,0.02735672,0.0000506204,0.00005479841,0.001300728,0.000181755,0.5817174,0.3680234,0.001940292,0.0183046,0.0001690347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07611985,0.00044626,0.9156898,0.0001114859,0.00007216824,0.0002390115,0.0001626755,0.004675704,0.00248309],"genre_scores_gemma":[0.4958761,0.0001991213,0.5009113,0.0001089081,0.00003358523,0.0001883383,0.0004322428,0.0002564122,0.00199394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001732932,"threshold_uncertainty_score":0.005065799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0234904686020716,"score_gpt":0.3030937157512211,"score_spread":0.2796032471491495,"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."}}