{"id":"W4413543380","doi":"10.64628/aam.u3smt34gx","title":"Apple Intelligence will help AI become as commonplace as word processing","year":2024,"lang":"en","type":"article","venue":"","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Computer science; Word (group theory); Natural language processing; Artificial intelligence; Linguistics; Philosophy","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":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002037115,0.0001868484,0.0001486841,0.0001694465,0.0001892965,0.001144371,0.001331315,0.00007282623,0.000891814],"category_scores_gemma":[0.00003378183,0.0001659171,0.00007403934,0.001000925,0.00004872187,0.002520015,0.0005440595,0.0004204235,0.005358632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136409,"about_ca_system_score_gemma":0.0002078357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004638535,"about_ca_topic_score_gemma":0.000222972,"domain_scores_codex":[0.9984413,0.00003828092,0.0002965845,0.000546155,0.0003378011,0.000339912],"domain_scores_gemma":[0.9988601,0.0002478723,0.00004410551,0.000587884,0.0001263558,0.0001336832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001241263,0.0001872231,0.0002704338,0.0002650451,0.00006107098,0.0002027154,0.008468663,0.0008966926,0.0005366454,0.3981162,0.04498559,0.5459973],"study_design_scores_gemma":[0.00004290293,0.0000984591,0.00003012781,0.0003184981,0.00001222489,0.0004066682,0.00110624,0.4308032,0.007694319,0.08130112,0.477746,0.0004402129],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002629998,0.0005612155,0.936882,0.02516385,0.001180855,0.0001895202,0.000002292835,0.001216382,0.03217394],"genre_scores_gemma":[0.9384336,0.00002949043,0.03723802,0.007133385,0.0001994477,0.0000587534,0.000006169199,0.00003160563,0.01686947],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9358037,"threshold_uncertainty_score":0.9998925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193453247741743,"score_gpt":0.3243022634326345,"score_spread":0.3049569386584602,"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."}}