{"id":"W4306160603","doi":"10.1177/00222437221134802","title":"Beyond Sentiment: The Value and Measurement of Consumer Certainty in Language","year":2022,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Certainty; Lexicon; Sentiment analysis; Valence (chemistry); Computer science; Consumer confidence index; Psychology; Natural language processing; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.006979869,0.0008600615,0.0008694043,0.004344378,0.0009675435,0.008864381,0.0008701008,0.001438065,0.004038005],"category_scores_gemma":[0.08054291,0.0004117931,0.0009169805,0.004812816,0.003388194,0.0144913,0.002784899,0.002315388,0.001136905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001427174,"about_ca_system_score_gemma":0.0005850549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002564069,"about_ca_topic_score_gemma":0.001604563,"domain_scores_codex":[0.9923909,0.003791729,0.0005192363,0.0008770756,0.002216962,0.0002040663],"domain_scores_gemma":[0.9528353,0.03199128,0.005920426,0.003712777,0.004899801,0.0006404367],"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":[0.001052703,0.0002715137,0.1736729,0.001559721,0.0009655307,0.0004126581,0.0115911,0.009154281,0.007821231,0.2413897,0.0206465,0.5314623],"study_design_scores_gemma":[0.0001054916,0.0005708748,0.1105887,0.001369655,0.0006169344,0.001020452,0.007796216,0.1151067,0.008862869,0.6781942,0.07526996,0.0004979633],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4452356,0.01175381,0.3833134,0.02261692,0.001572373,0.0004966137,0.004415445,0.001125625,0.1294701],"genre_scores_gemma":[0.9585373,0.001584981,0.03478379,0.001341466,0.0007633002,0.0001347233,0.0007802032,0.0001242704,0.001949959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008864381,"threshold_uncertainty_score":0.03691351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04945216976022157,"score_gpt":0.340007560906296,"score_spread":0.2905553911460744,"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."}}