{"id":"W3010530210","doi":"10.3389/fpsyg.2020.00341","title":"Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter","year":2020,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Identity, Memory, and Therapy","field":"Psychology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feeling; Psychology; Quarter (Canadian coin); Phenomenon; Social psychology; Social media; Period (music); Set (abstract data type); Demographics; Developmental psychology; Control (management); Demography; World Wide Web; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005579494,0.0001339138,0.00039081,0.00007293742,0.00004648471,0.00001070697,0.000432535,0.0001174463,0.0004653491],"category_scores_gemma":[0.00005386334,0.00008826381,0.00006399573,0.0002926934,0.0006803961,0.00004732816,0.00003837352,0.0002711408,0.0000146645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006110002,"about_ca_system_score_gemma":0.00001041576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002005729,"about_ca_topic_score_gemma":0.00001664287,"domain_scores_codex":[0.9983296,0.0005041819,0.0004937644,0.0003189381,0.000117783,0.0002356687],"domain_scores_gemma":[0.9991612,0.0001187545,0.0002179221,0.0004411774,0.00002619979,0.00003470355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.004486848,0.0004753435,0.03418002,0.00007910936,0.0006173517,0.00004779401,0.6819184,0.00001313076,0.001321429,0.02332913,0.1651527,0.0883788],"study_design_scores_gemma":[0.003775765,0.001358583,0.04083762,0.0000350841,0.0001640793,0.0000316914,0.7847371,0.0002535167,0.001151884,0.1627507,0.004417823,0.0004862314],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.884599,0.006342474,0.07062746,0.01787147,0.004265559,0.0005219759,0.0000151324,0.0000248372,0.01573211],"genre_scores_gemma":[0.991832,0.0001978047,0.0009169809,0.00674966,0.0002336111,0.00002596168,0.000002290577,0.00001660834,0.00002512575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1607348,"threshold_uncertainty_score":0.5095246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07725820256568149,"score_gpt":0.3512203666761191,"score_spread":0.2739621641104376,"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."}}