{"id":"W4393396017","doi":"10.1016/j.asoc.2024.111518","title":"SPINEX: Similarity-based predictions with explainable neighbors exploration for regression and classification","year":2024,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of Manitoba","funders":"","keywords":"Similarity (geometry); Regression; Artificial intelligence; Computer science; Pattern recognition (psychology); Machine learning; Statistics; Mathematics; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004785129,0.000155978,0.0001258898,0.0001652154,0.0005035647,0.0004950394,0.0002243453,0.0000739441,0.000001309134],"category_scores_gemma":[0.00004984594,0.0001283204,0.00002579455,0.0004471213,0.00004102151,0.0004933155,0.00006780639,0.0001902122,0.00000829613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004824656,"about_ca_system_score_gemma":0.00009418021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006078236,"about_ca_topic_score_gemma":0.000003016777,"domain_scores_codex":[0.9987396,0.0000372969,0.0002227294,0.0005883503,0.0001970314,0.0002149897],"domain_scores_gemma":[0.9990408,0.0003354764,0.0001040992,0.0003766161,0.00007133902,0.00007162823],"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":[0.0000428982,0.00007522214,0.000490889,0.0003729125,0.00002557176,0.000002816975,0.001400662,0.02013768,0.003876954,0.6849142,0.002137683,0.2865225],"study_design_scores_gemma":[0.0002931544,0.0000800245,0.001439289,0.0001208884,0.0000149954,0.000003821922,0.0001310635,0.9804194,0.0002907381,0.003447367,0.01360067,0.0001585836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002520161,0.0001028467,0.9920899,0.002961043,0.0001559258,0.0004152958,0.000004572624,0.0008232557,0.0009269937],"genre_scores_gemma":[0.8017746,0.000004324601,0.1976835,0.0001397779,0.0001034762,0.00008656587,0.0001497708,0.00001699256,0.00004108834],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9602817,"threshold_uncertainty_score":0.5232756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03046766081947922,"score_gpt":0.2814340144765215,"score_spread":0.2509663536570423,"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."}}