{"id":"W4391284316","doi":"10.5539/ijel.v13n7p96","title":"Italian Agri-Food Products Abroad: Word Formation Processes on Instagram","year":2023,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Linguistic Studies and Language Acquisition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Word (group theory); Advertising; Food science; Computer science; Industrial organization; Marketing; Chemistry; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001000923,0.0002800395,0.0001943773,0.002016562,0.001504558,0.002988444,0.0003021303,0.0004033829,0.004441446],"category_scores_gemma":[0.002796266,0.0001687678,0.0001829063,0.00293852,0.002022573,0.003363456,0.002103145,0.000886504,0.0007904081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001250433,"about_ca_system_score_gemma":0.0004484319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005619184,"about_ca_topic_score_gemma":0.01376289,"domain_scores_codex":[0.9992507,0.0003624532,0.00003198204,0.0001008485,0.0001620186,0.00009200823],"domain_scores_gemma":[0.9976104,0.001581351,0.0003904342,0.0001762235,0.0001633467,0.00007817305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002940793,0.00006529174,0.0473907,0.0002989783,0.00002212739,0.002170359,0.8310258,0.0001172258,0.01782818,0.02798396,0.004801049,0.06800219],"study_design_scores_gemma":[0.00001425365,0.00009736774,0.2607692,0.0001750804,0.00005807704,0.002830157,0.4750963,0.001485562,0.00797238,0.004064577,0.2473342,0.000102687],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9487008,0.0002991305,0.001300071,0.0006127337,0.00002675315,0.00002606325,0.0002554693,0.00004006407,0.04873881],"genre_scores_gemma":[0.992438,0.0002898262,0.001316547,0.00009118296,0.00004080281,0.0000288605,0.0003349138,0.00006232756,0.005397577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005619184,"threshold_uncertainty_score":0.01485813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01868815145991005,"score_gpt":0.2832416584811611,"score_spread":0.2645535070212511,"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."}}