{"id":"W4391986976","doi":"10.48550/arxiv.2402.11729","title":"Prospector Heads: Generalized Feature Attribution for Large Models & Data","year":2024,"lang":"en","type":"preprint","venue":"PubMed","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Office of Naval Research; U.S. Army Combat Capabilities Development Command; National Science Foundation; National Institutes of Health; VMware; Accenture","keywords":"Attribution; Feature (linguistics); Computer science; Pattern recognition (psychology); Artificial intelligence; Psychology; Social psychology; Philosophy; Linguistics","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"],"consensus_categories":[],"category_scores_codex":[0.001232225,0.0003207207,0.0003769787,0.0001532413,0.0001230487,0.0008205806,0.002934773,0.0004164082,0.000003497883],"category_scores_gemma":[0.0001128333,0.0002783442,0.0001853393,0.0003503797,0.00002665127,0.0004141222,0.003918744,0.0006321848,0.00002271621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291399,"about_ca_system_score_gemma":0.000182797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001314687,"about_ca_topic_score_gemma":0.00001096867,"domain_scores_codex":[0.9971858,0.00006918565,0.0003432096,0.001390463,0.0004127868,0.0005986162],"domain_scores_gemma":[0.9965503,0.00004117423,0.0001995534,0.002789241,0.0002766205,0.0001430817],"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":[0.00004458768,0.0002199867,0.00001596111,0.001067785,0.0001839914,0.000005268037,0.0001564344,0.00001645234,0.0002202028,0.5646882,0.2453743,0.1880068],"study_design_scores_gemma":[0.0004537728,0.00001352819,0.0006323348,0.00008915598,0.00009274563,0.000009635365,0.000001518865,0.1851801,0.006458755,0.4495177,0.3568149,0.0007358085],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00006995536,0.004219203,0.9763201,0.01033169,0.001344579,0.003652991,0.002215855,0.001422636,0.0004229513],"genre_scores_gemma":[0.2393784,0.002310807,0.6194175,0.002045408,0.003865085,0.05827397,0.01900413,0.0002636261,0.05544104],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3569026,"threshold_uncertainty_score":0.9999669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1461769294996707,"score_gpt":0.3215440342874362,"score_spread":0.1753671047877655,"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."}}