{"id":"W4402856813","doi":"10.5209/emp.97746","title":"From automata to algorithms: A jobs-to-be-done approach to AI in journalism","year":2024,"lang":"es","type":"article","venue":"Estudios sobre el Mensaje Periodístico","topic":"Hungarian Social, Economic and Educational Studies","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Journalism; Automaton; Computer science; Theoretical computer science; Algorithm; Artificial intelligence; Sociology; Media studies","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00174572,0.0006814852,0.00117356,0.0005000483,0.001367302,0.001446136,0.0009924374,0.0003244418,0.0002823015],"category_scores_gemma":[0.001068182,0.0007168061,0.0002819898,0.001914088,0.0003293878,0.0003782641,0.0006422352,0.0007315034,0.002866367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001751367,"about_ca_system_score_gemma":0.001373675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007892024,"about_ca_topic_score_gemma":0.001274881,"domain_scores_codex":[0.9946511,0.0004152333,0.001080581,0.001506651,0.0009719248,0.0013745],"domain_scores_gemma":[0.9974083,0.0006207619,0.0001300048,0.0005154157,0.0002321042,0.001093429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000955069,0.001075609,0.003721973,0.0001566165,0.001012283,0.0001084564,0.6758113,0.000387597,0.0001699044,0.02869881,0.2617742,0.02698772],"study_design_scores_gemma":[0.0008269703,0.0002569058,0.08505357,0.0007967098,0.0002817042,0.00001176477,0.1349608,0.0008946676,0.00001778976,0.002265174,0.7731602,0.001473805],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6470538,0.003891204,0.002185522,0.3027667,0.01141809,0.002719682,0.0008041848,0.0004327102,0.02872801],"genre_scores_gemma":[0.966455,0.0008906021,0.00777585,0.01104631,0.008987561,0.0006650248,0.00003629496,0.0001305995,0.004012759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5408505,"threshold_uncertainty_score":0.9999328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03659147713365873,"score_gpt":0.3432737598347894,"score_spread":0.3066822827011307,"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."}}