{"id":"W2298780090","doi":"10.14288/1.0069900","title":"Content analysis of online personal advertisements : attributes desired and offered","year":2010,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Advertising; Business; Internet privacy; Computer science; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.002321487,0.0001897625,0.0002773371,0.002748265,0.0004908232,0.00112942,0.0002524566,0.000207348,0.001922462],"category_scores_gemma":[0.01342258,0.0001006263,0.0002423234,0.00242011,0.0003912973,0.0006582421,0.0004980505,0.0003708116,0.0002312755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008637905,"about_ca_system_score_gemma":0.0008271663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002852978,"about_ca_topic_score_gemma":0.005244351,"domain_scores_codex":[0.9988702,0.0004180604,0.0001554967,0.00008231075,0.0004064023,0.00006751851],"domain_scores_gemma":[0.9836338,0.009912804,0.002328817,0.0004681097,0.003329955,0.0003265457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001429483,0.0007674792,0.682252,0.002339328,0.0001633864,0.0005181898,0.06296795,0.0004651411,0.0335216,0.002482374,0.00307021,0.2100229],"study_design_scores_gemma":[0.00002029798,0.0002286921,0.9661841,0.0001746599,0.0001022118,0.000353355,0.01840851,0.001410442,0.004430533,0.0007330133,0.00791717,0.00003725493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931526,0.0001176764,0.001032792,0.00005738833,0.00001616152,0.0003057112,0.001195007,0.00001642125,0.004106082],"genre_scores_gemma":[0.9894113,0.0002822443,0.006479086,0.00006994364,0.00004213358,0.0004969391,0.001538233,0.00002726814,0.001652889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002852978,"threshold_uncertainty_score":0.01227731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936432622187818,"score_gpt":0.222883118301507,"score_spread":0.1935187920796288,"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."}}