{"id":"W2613650556","doi":"10.1002/asi.23903","title":"Five decades of gratitude: A meta‐synthesis of acknowledgments research","year":2017,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Gratitude; Value (mathematics); Scopus; Context (archaeology); Scientific communication; Data science; Coding (social sciences); Scientific literature; Sociology; Library science; Social science; Computer science; Political science; History; Psychology; MEDLINE; Social psychology; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.08370727,0.001324788,0.004028584,0.03181236,0.001468655,0.008169224,0.001955349,0.00167027,0.003232712],"category_scores_gemma":[0.2099482,0.001178454,0.005249847,0.02658941,0.002756871,0.009727672,0.005279192,0.002859418,0.0002691585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00777314,"about_ca_system_score_gemma":0.01626968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003439962,"about_ca_topic_score_gemma":0.007607331,"domain_scores_codex":[0.9480467,0.03339911,0.009618384,0.003340736,0.004820567,0.0007745922],"domain_scores_gemma":[0.7552206,0.2115435,0.01158366,0.008248949,0.0123474,0.001055937],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.001019768,0.0001195536,0.01353986,0.4824137,0.04660915,0.000383841,0.07782526,0.001390933,0.001022855,0.03893568,0.01044965,0.3262898],"study_design_scores_gemma":[0.0001696062,0.0004630414,0.02153325,0.6766792,0.05944355,0.0003878871,0.05265667,0.0008786202,0.001151595,0.03090945,0.1555164,0.0002107231],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03501306,0.9329951,0.0120606,0.00954274,0.001903006,0.001004057,0.002653527,0.00009024564,0.004737642],"genre_scores_gemma":[0.3582299,0.6050436,0.02544669,0.004246661,0.0007633835,0.003180672,0.002174261,0.0001554326,0.0007594329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9681876,"threshold_uncertainty_score":0.4426916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5109254855075547,"score_gpt":0.5932061808176325,"score_spread":0.08228069531007787,"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."}}