{"id":"W4214861559","doi":"10.3390/axioms11030112","title":"Cubical Homology-Based Machine Learning: An Application in Image Classification","year":2022,"lang":"en","type":"article","venue":"Axioms","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Persistent homology; Topological data analysis; Artificial intelligence; Histogram; Pattern recognition (psychology); Topology (electrical circuits); Pixel; Homology (biology); Computer science; Digital image; Mathematics; Algorithm; Image processing; Image (mathematics); Biology; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004540607,0.00007089611,0.0001142669,0.000321204,0.0001712498,0.00004311101,0.0007835484,0.00003312233,0.0001479221],"category_scores_gemma":[0.00006295082,0.00006421177,0.00004080642,0.001984285,0.00004905836,0.0001982405,0.000230602,0.0002548604,0.00006915815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005609855,"about_ca_system_score_gemma":0.00002297644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000368436,"about_ca_topic_score_gemma":0.00003632477,"domain_scores_codex":[0.9988208,0.0002265296,0.000171583,0.0003971649,0.0002144497,0.0001694129],"domain_scores_gemma":[0.9993246,0.00007938048,0.00007582665,0.0004401999,0.00002091881,0.00005910493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004905131,0.001965484,0.03496671,0.000009487957,0.00002236869,0.00007814341,0.0004140064,0.008621247,0.01138336,0.5052424,0.0003327166,0.436915],"study_design_scores_gemma":[0.000254668,0.0002089526,0.06132508,3.019011e-7,0.00000465531,0.000006163697,0.00004517228,0.9241534,0.0001114422,0.002792548,0.0109804,0.0001171956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08762433,0.00006203453,0.9081842,0.003413771,0.00004651073,0.00009500512,0.000009540606,0.00013493,0.0004297036],"genre_scores_gemma":[0.9953777,0.000002907162,0.003814243,0.0003588609,0.00001494968,0.00009283669,0.0002256593,0.000003323473,0.0001095114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9155322,"threshold_uncertainty_score":0.261848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02071472068302907,"score_gpt":0.2666788035664304,"score_spread":0.2459640828834013,"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."}}