{"id":"W1597876521","doi":"10.1002/9781119959847.ch1","title":"“It Looks Great but How do I know if it Fits?”: An Introduction to Meta‐Synthesis Research","year":2011,"lang":"en","type":"other","venue":"","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Selection (genetic algorithm); Computer science; Qualitative research; Management science; Epistemology; Data science; Engineering ethics; Sociology; Engineering; Artificial intelligence; Social science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0531918,0.001424586,0.001851829,0.006083897,0.002036659,0.007146685,0.00246411,0.002968872,0.0196479],"category_scores_gemma":[0.07245659,0.001290392,0.001997586,0.01102579,0.004712136,0.008892049,0.003785722,0.006116908,0.00579706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004731487,"about_ca_system_score_gemma":0.008537688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002137816,"about_ca_topic_score_gemma":0.004472563,"domain_scores_codex":[0.9521816,0.04117999,0.002142287,0.001196251,0.003075349,0.0002245803],"domain_scores_gemma":[0.914861,0.0762258,0.001698046,0.002542457,0.004223467,0.0004493148],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000777366,0.00005766827,0.0002877422,0.01891597,0.0002888103,0.0001286715,0.01363266,0.001437957,0.000655339,0.5162089,0.1686393,0.2796692],"study_design_scores_gemma":[0.00002997412,0.00005222138,0.0004339074,0.01555213,0.00008085014,0.0001766167,0.002749531,0.001044378,0.0006227559,0.1927826,0.7864063,0.00006888617],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001824688,0.2730001,0.5140651,0.08472405,0.01195502,0.006372002,0.003727042,0.001193723,0.1031381],"genre_scores_gemma":[0.01972866,0.1952961,0.7152892,0.01698802,0.00271874,0.01763699,0.001635219,0.0009760683,0.02973104],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9468082,"threshold_uncertainty_score":0.2813085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2145971558398435,"score_gpt":0.4432425419013202,"score_spread":0.2286453860614767,"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."}}