{"id":"W2887275990","doi":"","title":"Research Guides: Graduate Specialist Program (New Brunswick Libraries): Text Analysis in R","year":2018,"lang":"en","type":"libguides","venue":"","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Library science; World Wide Web; Medical education; Computer science; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01187907,0.001864153,0.001915897,0.008596411,0.001468781,0.003939753,0.002729026,0.001572649,0.5631904],"category_scores_gemma":[0.1485085,0.0013794,0.0008228979,0.009262074,0.001221756,0.003444467,0.002610504,0.003531178,0.5090381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001741368,"about_ca_system_score_gemma":0.01253583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0102469,"about_ca_topic_score_gemma":0.02728786,"domain_scores_codex":[0.9926935,0.002669596,0.0007885056,0.001184096,0.002410198,0.0002540686],"domain_scores_gemma":[0.899258,0.04338896,0.003351114,0.01078207,0.03806207,0.005157812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004316891,0.00002598709,0.0001224991,0.000341356,0.000005461875,0.00001599414,0.0001097803,0.0001075346,0.0001677942,0.001638539,0.9492957,0.04812629],"study_design_scores_gemma":[0.0001207363,0.00004531301,0.001124525,0.0006858782,0.00002077685,0.00008067862,0.0002030684,0.001187902,0.001738731,0.009342271,0.9853987,0.00005147089],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002219595,0.002189385,0.1912492,0.02418674,0.005134435,0.003422605,0.3056747,0.1505168,0.3154067],"genre_scores_gemma":[0.01131014,0.003356374,0.2421553,0.005912283,0.001904496,0.01034782,0.1145483,0.108255,0.5022104],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5631904,"threshold_uncertainty_score":0.6230559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2368383316468401,"score_gpt":0.4900017841276578,"score_spread":0.2531634524808176,"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."}}