{"id":"W4416540783","doi":"10.2139/ssrn.5786806","title":"Explainable Artificial Intelligence and Machine Learning: Whatcha Talkin’ ’Bout, Willis?","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Counterfactual thinking; Structuring; Field (mathematics); Strengths and weaknesses; Artificial neural network; Deep learning; Comparability","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":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0129659,0.002001285,0.001961357,0.001640699,0.00369225,0.004506852,0.005896891,0.001260256,0.0002575233],"category_scores_gemma":[0.00157409,0.002127782,0.0008898688,0.002377168,0.0009155,0.002799848,0.00514092,0.02393463,0.0003668354],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004539193,"about_ca_system_score_gemma":0.01585386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002426736,"about_ca_topic_score_gemma":0.004986301,"domain_scores_codex":[0.9782604,0.001689294,0.003379656,0.003296575,0.001909501,0.01146458],"domain_scores_gemma":[0.9925402,0.0009077205,0.002175143,0.002002851,0.001442369,0.0009316564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002231797,0.0003910277,0.0002426417,0.0001967019,0.0005267284,0.0001349569,0.00400245,0.01985637,0.0001759374,0.6238883,0.00003152299,0.3503303],"study_design_scores_gemma":[0.0001658097,0.001500621,0.00001247651,0.0009227208,0.0002227945,0.001440934,0.01195105,0.1734679,0.006361813,0.791867,0.01032201,0.001764989],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00954774,0.03815293,0.9370015,0.006847284,0.004308271,0.001348239,0.00002134268,0.0003119559,0.002460769],"genre_scores_gemma":[0.8316361,0.1426815,0.00325523,0.0004422678,0.001607271,0.0001114194,0.00002996447,0.0001408511,0.02009537],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9337462,"threshold_uncertainty_score":0.9994817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03398647871139915,"score_gpt":0.2748793852795315,"score_spread":0.2408929065681324,"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."}}