{"id":"W2145727847","doi":"10.1093/her/cyl154","title":"Expanding our conceptualization of program implementation: lessons from the genealogy of a school-based nutrition program","year":2006,"lang":"en","type":"article","venue":"Health Education Research","topic":"Community Health and Development","field":"Health Professions","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre de Santé et de Services Sociaux Cavendish","funders":"","keywords":"Conceptualization; Construct (python library); Tracing; Process (computing); Nutrition Education; Situated; Program Design Language; Promotion (chess); Public relations; Sociology; Computer science; Political science; Medicine; Gerontology; Artificial intelligence; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003731142,0.0001179926,0.0002877703,0.0003259678,0.001561051,0.00001746594,0.0002941831,0.0001348716,0.0004084778],"category_scores_gemma":[0.0003924666,0.0001005052,0.00004624177,0.001169774,0.0001163433,0.00008506619,0.00008336414,0.0007240271,0.00003309495],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007144341,"about_ca_system_score_gemma":0.01758484,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05044407,"about_ca_topic_score_gemma":0.01138192,"domain_scores_codex":[0.9933531,0.003680509,0.001256666,0.000250904,0.0007307713,0.0007279954],"domain_scores_gemma":[0.9957323,0.001269224,0.0006159844,0.0005141335,0.001615719,0.0002526491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002656555,0.004941499,0.2516135,0.003879039,0.00002238918,2.280313e-7,0.01393816,0.00001238568,0.0002476059,0.01359019,0.317791,0.3936983],"study_design_scores_gemma":[0.00290393,0.0009422466,0.548574,0.001350234,0.00001020836,5.235074e-7,0.1812705,0.0001820708,0.0005581551,0.003956741,0.2600782,0.0001732136],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7750422,0.003923936,0.0006993033,0.1940833,0.001147331,0.02309964,0.0002048891,0.0002016925,0.001597711],"genre_scores_gemma":[0.9751272,0.0004061325,0.01048869,0.001579614,0.0005455132,0.009441177,0.002212096,0.00002472339,0.0001748505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3935251,"threshold_uncertainty_score":0.9997388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4586744670053061,"score_gpt":0.6912363065641249,"score_spread":0.2325618395588189,"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."}}