{"id":"W6966791941","doi":"10.48448/gms8-c773","title":"Semantic are Beacons: A Semantic Perspective for Unveiling Parameter-Efficient Fine-Tuning in Knowledge Learning","year":2024,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Perspective (graphical); Semantics (computer science); Semantic memory; Adaptation (eye); Semantic network; Knowledge extraction","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003439158,0.0009878972,0.001190163,0.00585916,0.0004326576,0.0005989616,0.001347751,0.0004337907,0.0001946033],"category_scores_gemma":[0.004020728,0.0009568399,0.0002938535,0.00529827,0.001824142,0.000196135,0.0006860552,0.001663609,0.003859776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002124147,"about_ca_system_score_gemma":0.001593634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006289499,"about_ca_topic_score_gemma":0.005048362,"domain_scores_codex":[0.9932692,0.0002202352,0.0008695852,0.002734099,0.00108214,0.001824752],"domain_scores_gemma":[0.9967304,0.0007474755,0.0007452393,0.0008962479,0.0005520707,0.0003285277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006799352,0.01160351,0.008888709,0.02318066,0.002877033,0.002837574,0.1305332,0.2912537,0.05980955,0.1574438,0.2828896,0.02800271],"study_design_scores_gemma":[0.001277375,0.0002899312,0.00004991187,0.009172011,0.0003106742,0.00006273632,0.02265037,0.9365489,0.0002462277,0.002825078,0.02486555,0.00170126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04906946,0.08021455,0.08048204,0.002274523,0.01281542,0.02041171,0.001231118,0.01187065,0.7416305],"genre_scores_gemma":[0.7937937,0.00004219508,0.01138559,0.00005746253,0.0008302436,0.0003354028,0.00006802237,0.002543591,0.1909438],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7447242,"threshold_uncertainty_score":0.9992882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03895416247765882,"score_gpt":0.3455354082978626,"score_spread":0.3065812458202037,"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."}}