{"id":"W4398163620","doi":"10.1016/j.ipm.2024.103765","title":"Predicting users’ future interests on social networks: A reference framework","year":2024,"lang":"en","type":"article","venue":"Information Processing & Management","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; Toronto Metropolitan University; University of Guelph","funders":"University of Guelph","keywords":"Computer science; Data science; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001604442,0.001368416,0.0009989296,0.004271874,0.0007731653,0.00179054,0.001511342,0.001313142,0.001810832],"category_scores_gemma":[0.006562024,0.0003487932,0.0009627265,0.003404125,0.0005121151,0.003895627,0.001131513,0.001217357,0.001286311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104274,"about_ca_system_score_gemma":0.0006719717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01547846,"about_ca_topic_score_gemma":0.01740545,"domain_scores_codex":[0.998839,0.0004574982,0.0000628667,0.0003722825,0.000170082,0.00009837716],"domain_scores_gemma":[0.9969146,0.001502577,0.0003378507,0.0005223553,0.0005579136,0.0001646091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007564071,0.000886229,0.1066496,0.0007995951,0.0005775647,0.0008519044,0.001374785,0.4069099,0.006186655,0.04549178,0.01565536,0.4138602],"study_design_scores_gemma":[0.00001163026,0.0001360162,0.009082678,0.00005156101,0.00008027273,0.0001785176,0.0001365509,0.9697851,0.0009266664,0.01488048,0.004703382,0.00002713501],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.288717,0.01090815,0.6672397,0.003364884,0.000186775,0.0004470334,0.01013514,0.002134945,0.01686624],"genre_scores_gemma":[0.9144599,0.002352599,0.07333293,0.0001520967,0.000305503,0.0002437678,0.005645529,0.00007601981,0.003431692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01547846,"threshold_uncertainty_score":0.03077674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02314745026922628,"score_gpt":0.3175364054326009,"score_spread":0.2943889551633746,"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."}}