{"id":"W3206390449","doi":"10.1108/jqme-10-2020-0109","title":"Models for maintenance planning and scheduling – a citation-based literature review and content analysis","year":2021,"lang":"en","type":"article","venue":"Journal of Quality in Maintenance Engineering","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Citation; Co-citation; Thematic analysis; Computer science; Exploratory analysis; Data science; Scheduling (production processes); Citation analysis; Operations research; Management science; Engineering; Operations management; Sociology; Social science; Qualitative research; Library science","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":[],"consensus_categories":[],"category_scores_codex":[0.001450052,0.0001945238,0.0006821058,0.0002842329,0.00003169142,0.0000764397,0.00008787223,0.00009382698,0.000001795956],"category_scores_gemma":[0.00136871,0.0001788499,0.000168163,0.0007934219,0.00002728597,0.0004084138,0.00001585728,0.0003358973,5.947315e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001189519,"about_ca_system_score_gemma":0.00003993224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000214941,"about_ca_topic_score_gemma":0.000005153854,"domain_scores_codex":[0.9984619,0.00004796204,0.0008493764,0.0001948072,0.0001624584,0.0002834701],"domain_scores_gemma":[0.9986216,0.0003515076,0.0001884877,0.0001585696,0.0005783127,0.0001015631],"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":[0.00002181958,0.00001419673,0.0005090552,0.003028546,0.000148578,0.0000265658,0.0003994944,0.9928714,0.0007932715,0.001707095,0.00005037802,0.0004296112],"study_design_scores_gemma":[0.000871675,0.00002972337,0.002546537,0.006711257,0.0002304574,0.00004599958,0.0003596802,0.9880188,0.0001970168,0.0005932602,0.0001562812,0.0002393289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04586285,0.06098612,0.8915734,0.001149266,0.0001473884,0.0002074274,0.0000207594,0.00003248131,0.00002031047],"genre_scores_gemma":[0.8279816,0.02234232,0.1488928,0.0005936594,0.00006285522,0.00003587967,0.00002142998,0.00003731501,0.00003214095],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7821187,"threshold_uncertainty_score":0.7293286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0379132787457484,"score_gpt":0.2849896022973017,"score_spread":0.2470763235515533,"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."}}